Dr Julia Bohlius
email: jbohlius@ispm.unibe.ch

Kurt Schmidlin

Dominique Costagliola

Gerd Fätkenheuer

Margaret May

Ana Maria Caro-Murillo

Amanda Mocroft

Fabrice Bonnet

Gary Clifford

Anastasia Karafoulidou

Incidence and risk factors of HIV-related non-Hodgkin's lymphoma in the era of combination antiretroviral therapy: a European

Keywords: non-Hodgkin lymphoma, cohort studies, antiretroviral therapy, Kaposi sarcoma, immunodeficiency, viral load, Europe

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Human immunodeficiency virus (HIV)-infected patients are at increased risk of developing non-Hodgkin Lymphoma (NHL) when compared to the general population [START_REF] Dal Maso | Epidemiology of non-Hodgkin lymphomas and other haemolymphopoietic neoplasms in people with AIDS[END_REF][START_REF] Frisch | Association of cancer with AIDSrelated immunosuppression in adults[END_REF]. In the 1980s the risk of NHL within three years of an AIDS diagnosis was increased 165-fold when compared to people without AIDS [START_REF] Cote | Non-Hodgkin's lymphoma among people with AIDS: incidence, presentation and public health burden. AIDS/Cancer Study Group[END_REF].

Following its introduction in 1996, combination antiretroviral therapy (cART) has led to a substantial reduction in HIV-associated morbidity and mortality; however, cohort studies have shown that the decline in the incidence of NHL in the cART era was less pronounced than that observed for Kaposi's Sarcoma (KS) or opportunistic infections [START_REF] Ledergerber | AIDS-related opportunistic illnesses occurring after initiation of potent antiretroviral therapy: the Swiss HIV Cohort Study[END_REF][START_REF] Engels | Cancer risk in people infected with human immunodeficiency virus in the United States[END_REF][START_REF] Crum-Cianflone | Trends in the incidence of cancers among HIV-infected persons and the impact of antiretroviral therapy: a 20-year cohort study[END_REF][START_REF] Long | Incidence and outcomes of malignancy in the HAART era in an urban cohort of HIV-infected individuals[END_REF]. Consequently NHL has become one of the most frequent AIDS-defining events in recent years [START_REF] Arminio | The changing incidence of AIDS events in patients receiving highly active antiretroviral therapy[END_REF] and the most common cancer associated with HIV in the USA [START_REF] Long | Incidence and outcomes of malignancy in the HAART era in an urban cohort of HIV-infected individuals[END_REF]. In HIV-infected patients NHL poses particular therapeutic challenges [START_REF] Spano | AIDS-related malignancies: state of the art and therapeutic challenges[END_REF] and continues to be an important cause of death in the era of cART [START_REF] Bonnet | Changes in cancer mortality among HIVinfected patients: the Mortalite 2005 Survey[END_REF].

Previous studies showed that the risk of NHL in HIV-infected persons is increased in older patients [START_REF] Kirk | Non-Hodgkin lymphoma in HIV-infected patients in the era of highly active antiretroviral therapy[END_REF][START_REF] Stebbing | Antiretroviral treatment regimens and immune parameters in the prevention of systemic AIDS-related non-Hodgkin's lymphoma[END_REF][START_REF] Polesel | Non-Hodgkin lymphoma incidence in the Swiss HIV Cohort Study before and after highly active antiretroviral therapy[END_REF][START_REF] Zoufaly | Insufficient Virus Suppression during HAART Is a Strong Predictor for the Development of AIDS-related Lymphoma: German CLINSURV Cohort[END_REF], in patients with more advanced immunodeficiency [START_REF] Kirk | Non-Hodgkin lymphoma in HIV-infected patients in the era of highly active antiretroviral therapy[END_REF][START_REF] Stebbing | Antiretroviral treatment regimens and immune parameters in the prevention of systemic AIDS-related non-Hodgkin's lymphoma[END_REF][START_REF] Polesel | Non-Hodgkin lymphoma incidence in the Swiss HIV Cohort Study before and after highly active antiretroviral therapy[END_REF][START_REF] Zoufaly | Insufficient Virus Suppression during HAART Is a Strong Predictor for the Development of AIDS-related Lymphoma: German CLINSURV Cohort[END_REF][START_REF] Biggar | AIDS-related cancer and severity of immunosuppression in persons with AIDS[END_REF] and patients with high HIV-1 viral loads [START_REF] Kirk | Non-Hodgkin lymphoma in HIV-infected patients in the era of highly active antiretroviral therapy[END_REF][START_REF] Zoufaly | Insufficient Virus Suppression during HAART Is a Strong Predictor for the Development of AIDS-related Lymphoma: German CLINSURV Cohort[END_REF]. Many of these studies were, however, from the pre-cART era or lacked information on cART at the patient level [START_REF] Engels | Cancer risk in people infected with human immunodeficiency virus in the United States[END_REF]. Only a few, relatively small studies specifically addressed risk factors for NHL in patients receiving cART [START_REF] Kirk | Non-Hodgkin lymphoma in HIV-infected patients in the era of highly active antiretroviral therapy[END_REF][START_REF] Polesel | Non-Hodgkin lymphoma incidence in the Swiss HIV Cohort Study before and after highly active antiretroviral therapy[END_REF][START_REF] Zoufaly | Insufficient Virus Suppression during HAART Is a Strong Predictor for the Development of AIDS-related Lymphoma: German CLINSURV Cohort[END_REF].

We analyzed the database of the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) to examine the incidence and risk factors of NHL in the cART era.

Methods

COHERE is a collaboration of 33 observational cohort studies in 30

European countries [START_REF]of Observational HIV Epidemiological Research Europe (COHERE) Study Group. Response to combination antiretroviral therapy: variation by age[END_REF]. COHERE was established in 2005 with the objective of conducting hypothesis-driven research on the prognosis and outcome of HIVinfected individuals across Europe. All cohorts have been approved by local ethics committees or institutional review boards, use standardized methods of data collection, and schedule follow-up visits at least once every 6 months. Each cohort submits information using the standardized HIV Collaboration Data Exchange Protocol (HICDEP) [START_REF] Kjaer | HIV cohort collaborations: proposal for harmonization of data exchange[END_REF]

Inclusion criteria and definitions

We included all adult (aged 16 years or older) antiretroviral treatmentnaïve HIV-infected patients enrolled in COHERE cohorts who started cART at some point after 1 January 1998, at a time when cART had become well established and widely used in Europe. All patients had to have at least one CD4 cell measurement after enrolment and before starting cART. In patients developing NHL, the CD4 count had to be measured before the diagnosis of NHL. Baseline CD4 cell count was defined as the first CD4 count measured during a visit after 1 January 1998. The baseline HIV-1 RNA was taken as the measurement closest to the baseline CD4 cell count, within a window of plus or minus 30 days not on cART. The nadir CD4 cell count was defined as the lowest ever measured CD4 cell count up to seven days after starting cART. In patients who developed NHL before starting cART, the nadir CD4 count had to be measured before the diagnosis of NHL. We defined cART as a regimen with at least 3 antiretroviral drugs from any drug class, including protease inhibitors (PIs), nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs) and fusion inhibitors. Data were merged on 31 July 2006.

The diagnosis of NHL was made on the basis of the 1993 CDC (Centers for Disease Control and Prevention) histology criteria [START_REF]1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults[END_REF]. Burkitt's lymphoma, immunoblastic lymphoma and primary brain lymphoma (PBL) are included in the CDC definition. We included all subtypes of NHL including unspecified and other types in our analysis. However, information on subtypes was incomplete in many cohorts, except for the distinction between PBL and systemic NHL. We therefore restricted the analysis to comparisons between PBL and systemic NHL. For patients in clinical CDC stage C (AIDS) at baseline we distinguished between patients with a history of Kaposi Sarcoma and patients with a history of another AIDS-defining illness: Kaposi Sarcoma may be associated with an increased risk of some subtypes of NHL in HIV-infected patients [START_REF] Engels | Cancers associated with Kaposi's sarcoma (KS) in AIDS: a link between KS herpesvirus and immunoblastic lymphoma[END_REF][START_REF] Deloose | High incidence of Kaposi sarcoma-associated herpesvirus infection in HIV-related solid immunoblastic/plasmablastic diffuse large B-cell lymphoma[END_REF][START_REF] Chadburn | KSHVpositive solid lymphomas represent an extra-cavitary variant of primary effusion lymphoma[END_REF].

Statistical analysis

The incidence rate of systemic NHL and PBL was calculated by dividing the number of patients developing the disease by the number of person-years at risk. In patients not on cART we measured time from the date of the first visit with a CD4 cell count after 1 January 1998 (baseline) until the date of NHL diagnosis, start of cART or the last follow-up visit, whichever came first. In patients on cART we measured time from the start of cART until the diagnosis of NHL or the last follow-up visit. We used an intent-to-continue-treatment approach and thus ignored subsequent changes to treatment, including treatment interruptions and terminations. Prevalent cases, i.e. patients with NHL at baseline, were excluded.

We identified risk factors for developing systemic NHL using Weibull models, with random-effects to account for heterogeneity between cohort studies. The number of PBL cases was too small to allow meaningful analyses.

Multivariable models included age and CDC clinical stage (at baseline or at start of cART), sex, transmission risk group, and nadir CD4 counts. Variables were included in the model based on biological and statistical reasoning; no automated selection procedure was applied. The effect of changes in CD4 cell counts and plasma HIV-1 RNA load over time were explored in time-updated models.

Results are presented as medians with interquartile ranges (IQR), incidence rates per 100,000 person-years with 95% confidence intervals (CIs), Kaplan-Meier estimates of the cumulative incidence of NHL and crude and adjusted hazard ratios (HRs) with 95% CIs. All statistical analyses were done in Stata (version 10, StataCorp, College Station, Texas).

Results

Characteristics of cohorts and patients

The database included a total of 67,659 patients, including 1,176 patients who had been diagnosed with NHL. Of note, among patients with NHL, 660 (56.1%) had been diagnosed while not on cART. A total of 11,354 (16.8%) patients were excluded from the analysis for the reasons detailed in Figure 1.

The most important reasons for exclusion were missing CD4 counts between 01.01.1998 and the start of cART or the diagnosis of NHL. Of note, this group included many patients who were diagnosed with NHL and enrolled in the cohort around the same time, i.e. patients with prevalent NHL. Patients not diagnosed with NHL and excluded because of missing CD4 counts were more likely to have a history of intravenous drug use (27% versus 17%) and of AIDS compared to included patients (26% versus 18%); patients were similar with respect to age and gender. Among patients with NHL those who were excluded had more often been diagnosed with AIDS before developing NHL compared to included patients (22% versus 14%), but they were similar with respect to age, gender and risk group.

A total of 56,305 patients (83%) were included in analyses. The median date of the last follow up was June 1, 2005 (IQR May 11, 2004 to December 21, 2005). The characteristics of the included patients are shown in Table 1. Median age was 36.1 years, and most patients were male (n=40,350, 72%). Overall, heterosexual contacts were the most frequent risk factor for HIV transmission, followed by sex between men and injection drug use. The median baseline CD4 cell count was 192 cells/μL and the median plasma HIV-1 RNA load 75,001 copies/mL. Overall 10,382 (18%) of patients were in CDC clinical stage C at baseline. Among 1,186 patients with a history of KS, 747 (63%) were men who had sex with men (MSM).

During 212,042 person-years of follow-up, 583 patients were diagnosed with NHL, including 62 (11%) cases of PBL and 521 cases (89%) of systemic NHL. Among the latter, 382 (73%) lymphomas were classified as not specified and 36 (7%) as other; 60 patients (12%) were diagnosed with a Burkitt's lymphoma and 43 (8%) with a diffuse large cell lymphoma. Twenty-nine patients had a KS diagnosed prior to the diagnosis of NHL. The median time between the diagnosis of KS and NHL was 293 days (IQR 65 to 679 days). Compared to patients who did not develop NHL, patients diagnosed with NHL were older, more likely to be male, and more likely to be in more advanced stages of the infection, with lower CD4 cell counts and higher plasma HIV-1 RNA loads at baseline (Table 1). Patients on cART at the time of systemic NHL diagnosis were more often in advanced clinical stage (26% versus 12% in CDC clinical stage C) and had lower CD4 cell counts (median 164 cells/µL versus 187 cells/µL) compared to cART naïve patients. As expected, patients who had not been on cART had higher HIV-1 RNA viral loads (Table 4).

Incidence of NHL while not on cART and on cART

A total of 155 systemic NHL were diagnosed while not on cART and 366 were diagnosed on cART. The incidence rate was 462.6 (95% CI 395.3 to 541.5) per 100,000 person-years not on cART and 205.1 (95% CI 185.1 to 227.2) per 100,000 person-years in treated patients, for a rate ratio of 0.44 (95% CI 0.37 to 0.53). There were 19 diagnoses of PBL in patients not on cART and 43 diagnoses of PBL on cART. The incidence rate was 56.7 (95% CI 36.2 to 88.9) per 100,000 person-years not on cART and 24.1 (95% CI 17.9 to 32.5) per 100,000 person-years on cART, for a rate ratio of 0.43 (95% CI 0.25 to 0.73).

Overall the median time from the start of observation to the diagnosis was 81 days (IQR 18 to 707 days) while not on cART, and 287 days (IQR 82-860 days) while on cART. In sensitivity analyses incidence rates were similar when including the patients with missing CD4 counts, but excluding prevalent cases.

Figure 2 shows that incidence rates for any type of NHL declined with increasing nadir CD4 counts and decreasing baseline HIV-1 RNA viral load. These trends were particularly pronounced in patients not on cART. Figure 3 shows the cumulative incidence of any NHL (systemic NHL and PBL) after start of cART by nadir CD4 cell count. Overall 1.21% (95% CI 1.09% -1.34%) of patients had developed a systemic NHL or PBL at five years after starting cART. The cumulative incidence at five years was higher in patients with nadir CD4 cell counts <50 cells/µL (1.86%, 95% CI 1.53% -2.25%) compared to patients with nadir CD ≥ 350 cells/ µL (0.43%, 95% CI 0.29% -0.63%).

Risk factors for systemic NHL while not on cART and on cART

In univariable analysis the incidence rate while not on cART was higher in men than in women, higher in men who have sex with men than in other transmission groups (i.e. injection-drug use and heterosexual contacts) and higher among patients aged 50 years or older, patients with a history of KS, patients with nadir CD4 cell counts below 100 cells/µ L and patients with baseline HIV-RNA plasma loads of 100,000 copies/mL or greater (Table 2). Differences in the same direction were observed in patients developing NHL on cART.

In multivariable analyses treating CD4 counts and HIV-1 viral load as timeupdated variables (Table 3) associations with age, CD4 cell count and HIV-1 viral load remained both for systemic NHL diagnosed while not on cART and for systemic NHL diagnosed on cART. A history of KS and transmission group men who have sex with men were additional risk factors in patients on cART. There was little evidence for a difference in risk across cART regimens (PI-based, NNRTI-based or NRTIs only).

Discussion

The incidence of HIV-associated NHL in patients receiving cART was lower than in patients not on cART, with reductions in incidence rate of over 50% both for systemic NHL and PBL. A history of advanced immunodeficiency and older age were associated with an increased risk of systemic NHL both in patients receiving and not receiving cART. In patients on cART, a prior diagnosis of KS and transmission through sex between men was also associated with NHL.

Exposure to high plasma HIV-1 RNA concentrations and low CD4 cell counts were risk factors in patients not receiving cART. Conversely, suppression of HIV-1 replication and immune recovery were protective factors in patients receiving cART. Our results thus support the notion that both immunodeficiency and replication of HIV-1 play a role in the development of NHL [START_REF] Polesel | Non-Hodgkin lymphoma incidence in the Swiss HIV Cohort Study before and after highly active antiretroviral therapy[END_REF][START_REF] Zoufaly | Insufficient Virus Suppression during HAART Is a Strong Predictor for the Development of AIDS-related Lymphoma: German CLINSURV Cohort[END_REF][START_REF] Bonnet | Factors associated with the occurrence of AIDS-related non-Hodgkin lymphoma in the era of highly active antiretroviral therapy: Aquitaine Cohort, France[END_REF].

Our study has several limitations. The analysis was restricted to patients with CD4 cell counts available before the start of cART and prior to the diagnosis of NHL. This meant that some patients were excluded from the analysis, although incidence rates were similar when they were included in sensitivity analyses. In the majority of cases the histological subtype was not specified and we could therefore only distinguish between systemic NHL and PBL. The number of patients developing PBL was small even in this large collaborative study.

Finally, cART naïve patients who developed NHL and died before starting cART were not included in the present data set. This may have lead to an underestimation of the incidence rate of NHL in patients not on cART. On the other hand, our analysis of patients on cART may have included periods where cART was interrupted, leading to overestimation of the incidence rate of NHL on cART.

Previous studies have shown a decline in the incidence of HIV-related NHL when comparing the pre-cART and cART eras [START_REF] Biggar | AIDS-related cancer and severity of immunosuppression in persons with AIDS[END_REF][START_REF]Highly active antiretroviral therapy and incidence of cancer in human immunodeficiency virus-infected adults[END_REF]. The interpretation of these comparisons is, however, not straightforward because the treatment status of the individual patient was not known [START_REF] Biggar | AIDS-related cancer and severity of immunosuppression in persons with AIDS[END_REF][START_REF]Highly active antiretroviral therapy and incidence of cancer in human immunodeficiency virus-infected adults[END_REF]. As our study shows, the availability of cART does not mean that all patients actually receive cART: in our study about 50% of patients (before exclusions) were not on cART when diagnosed with NHL. Similar data were reported both in other cohort studies [START_REF] Hoffmann | Response to highly active antiretroviral therapy strongly predicts outcome in patients with AIDS-related lymphoma[END_REF][START_REF] Antinori | Better response to chemotherapy and prolonged survival in AIDS-related lymphomas responding to highly active antiretroviral therapy[END_REF][START_REF] Simcock | Treatment and prognosis of AIDS-related lymphoma in the era of highly active antiretroviral therapy: findings from the Swiss HIV Cohort Study[END_REF] and clinical trials [START_REF] Boue | Phase II trial of CHOP plus rituximab in patients with HIV-associated non-Hodgkin's lymphoma[END_REF].

Our data confirm that exposure to low CD4 cell counts is the main risk factor for developing NHL [START_REF] Kirk | Non-Hodgkin lymphoma in HIV-infected patients in the era of highly active antiretroviral therapy[END_REF][START_REF] Stebbing | Antiretroviral treatment regimens and immune parameters in the prevention of systemic AIDS-related non-Hodgkin's lymphoma[END_REF][START_REF] Polesel | Non-Hodgkin lymphoma incidence in the Swiss HIV Cohort Study before and after highly active antiretroviral therapy[END_REF][START_REF] Zoufaly | Insufficient Virus Suppression during HAART Is a Strong Predictor for the Development of AIDS-related Lymphoma: German CLINSURV Cohort[END_REF][START_REF] Biggar | AIDS-related cancer and severity of immunosuppression in persons with AIDS[END_REF] but within categories of similar CD4 cell nadirs, cART treated patients had a lower risk of NHL compared to patients not on cART. Of note, a diagnosis of AIDS was not associated with an increased risk of NHL after adjusting for nadir CD4 cells count. However, we found that a history of KS was a significant risk factor in patients on cART, after adjusting for transmission group and other risk factors in multivariable analysis.

Pathways that may be involved in the development of lymphoma in HIVinfected patients include immunosuppression, chronic B-cell stimulation and transformation caused by other co-infecting viruses, such as Epstein Barr virus (EBV) and human herpes virus 8 (HHV-8) [START_REF] Grulich | B-cell stimulation and prolonged immune deficiency are risk factors for non-Hodgkin's lymphoma in people with AIDS[END_REF][START_REF] Lim | Recent advances in acquired immunodeficiency syndrome (AIDS)-related lymphoma[END_REF][START_REF] Sullivan | HIV/AIDS: epidemiology, pathophysiology, and treatment of Kaposi sarcoma-associated herpesvirus disease: Kaposi sarcoma, primary effusion lymphoma, and multicentric Castleman disease[END_REF][START_REF] Carbone | HIV-associated lymphomas and gamma-herpesviruses[END_REF]. The association between HHV-8 and KS, and the rare multicentric Castleman disease and primary effusion lymphoma is well established while a possible association with other lymphoproliferative disorders is a matter of ongoing debate [START_REF] Carbone | HIV-associated lymphomas and gamma-herpesviruses[END_REF][START_REF] Du | Kaposi sarcoma-associated herpesvirus/human herpesvirus 8 and lymphoproliferative disorders[END_REF][START_REF] Oksenhendler | High incidence of Kaposi sarcoma-associated herpesvirus-related non-Hodgkin lymphoma in patients with HIV infection and multicentric Castleman disease[END_REF][START_REF] Chang | Identification of herpesvirus-like DNA sequences in AIDS-associated Kaposi's sarcoma[END_REF][START_REF] Cesarman | Kaposi's sarcomaassociated herpesvirus-like DNA sequences in AIDS-related body-cavity-based lymphomas[END_REF][START_REF] Hjalgrim | Infectious aetiology of Hodgkin and non-Hodgkin lymphomas: a review of the epidemiological evidence[END_REF]. Results from previous studies suggested an increased risk of specific subtypes of NHL in HIVinfected patients diagnosed with KS [START_REF] Engels | Cancers associated with Kaposi's sarcoma (KS) in AIDS: a link between KS herpesvirus and immunoblastic lymphoma[END_REF][START_REF] Deloose | High incidence of Kaposi sarcoma-associated herpesvirus infection in HIV-related solid immunoblastic/plasmablastic diffuse large B-cell lymphoma[END_REF][START_REF] Ridolfo | High frequency of non-Hodgkin's lymphoma in patients with HIV-associated Kaposi's sarcoma[END_REF][START_REF] Biggar | Risk of other cancers following Kaposi's sarcoma: relation to acquired immunodeficiency syndrome[END_REF][START_REF] Engels | Immunoblastic lymphoma in persons with AIDS-associated Kaposi's sarcoma: a role for Kaposi's sarcoma-associated herpesvirus[END_REF][START_REF] Martin-Carbonero | Long-term prognosis of HIVinfected patients with Kaposi sarcoma treated with pegylated liposomal doxorubicin[END_REF]. Our results provide some support for the hypothesis that HHV-8 may contribute to the development of NHL. However, patients with a malignant disease are generally at increased risk of developing secondary NHL and other malignancies, which may be related to exposure to chemotherapy and genetic factors [START_REF] Krishnan | Non-Hodgkin lymphoma secondary to cancer chemotherapy[END_REF]. Further studies are needed to clarify a possible role of HHV-8 and specific subtypes of HIV-associated NHL. The CD4 cell count at which cART should be initiated is a central but unresolved issue in the care of HIV-1 infected patients. The results of our study are relevant to this debate: the strong relationship between exposure to low CD4 cell counts and the risk of NHL, and the protective effect of suppressing HIV-1 replication supports the move towards earlier initiation of cART. In the SMART randomized controlled trial the incidence of malignancies was higher in the drug conservation arm in which cART was stopped if the CD4 cell count exceeded 350 cells/µL and restarted if it fell to less than 250 cells/µL, compared to the viral suppression arm utilizing continuous cART [START_REF] Silverberg | Risk of cancers during interrupted antiretroviral therapy in the SMART study[END_REF]. The International AIDS Society USA Panel recommends that antiretroviral therapy is started in individuals whose CD4 count drops below 350 cells/µL, and that the decision should be individualized in patients with CD4 counts above 350 cells/µL [START_REF] Hammer | Antiretroviral treatment of adult HIV infection: 2008 recommendations of the International AIDS Society-USA panel[END_REF]. Of note, in our analysis the risk of NHL was higher in patients with nadir CD4 counts in the range of 200 to 349 cells/µL compared to patients with nadir counts above 350 cells cells/µL. This might be particularly important in patients aged 50 years or older, given their increased risk of NHL, and slower immune recovery.

In conclusion, the risk of HIV-related NHL is more than halved in patients on cART. Timely initiation of cART followed by suppression of HIV replication and immune recovery are key factors to prevent NHL in the era of cART. The association with Kaposi Sarcoma suggests a role of HHV-8 in HIV-associated NHL, which needs further investigation. All variables except nadir CD4 count were measured at baseline for the analysis of patients not on cART and at the start of cART for the analysis of patients on cART.

  to co-ordinating centres at the Copenhagen HIV Program (CHIP), Copenhagen, Denmark, or the Institut de Santé Publique d'Épidémiologie et de Développement (ISPED), Bordeaux, France. Data collected include information on patient demographics, use of cART, CD4 cell counts and percentages, HIV-1 RNA concentrations (viral loads), AIDS and deaths. Further information is given at http://www.chip.dk/COHERE/tabid/295/Default.aspx and http://etudes.isped.u-bordeaux2.fr/cohere/. Twenty-two cohorts from ten countries contributed data to the present analyses.

Figure 2 -Figure 3 -

 23 Figure 2 -Incidence rate of any type of non-Hodgkin lymphoma (systemic NHL and PBL) across categories of baseline CD4 cell count (upper panel) and HIV-1 viral load (lower panel) in patients on cART and not on cART

Table 1 :

 1 Patient characteristics at baseline

		Patients diagnosed with NHL	Patients not diagnosed with NHL	P
		(n=583)	(n=55,722)
	Type of NHL
	Systemic NHL	521 (89%)	-
	PBL	62 (11%)	-
	Age (years) at baseline			<0.0001
	Median (IQR)	39.3 (34.0 to 47.5)	36.1 (30.9 to 42.4)
	16-29	62 (11%)	11,818 (21%)
	30-39	240 (41%)	25,606 (46%)
	40-49	160 (27%)	12,061 (22%)
	≥ 50	121 (21%)	6,237 (11%)
	Sex			<0.0001
	Women	109 (19%)	15,846 (28%)
	Men	474 (81%)	39,876 (72%)
	Transmission risk group			<0.0001
	Injection-drug use	89 (15%)	9,377 (17%)
	MSM	242 (42%)	18,249 (33%)
	Heterosexual	196 (34%)	22,707 (41%)
	Other / unknown	56 (10%)	5,389 (10%)
	CDC clinical stage
	Stage A / B	446 (77%)	45,477 (82%)	<0.0001
	Stage C without KS	108 (19%)	9,088 (16%)
	Stage C with KS	29 (5%)	1,157 (2%)
	Nadir CD4 cell count (cells/µ L)			<0.0001
	Median (IQR)	111 (43 to 217)	193 (82 to 308)
	< 50	161 (28%)	9,678 (17%)
	50-99	103 (18%)	6,249 (11%)
	100-199	149 (26%)	12,705 (23%)
	200-349	118 (20%)	16,424 (29%)
	≥ 350	52 (9%)	10,666 (19%)
	Plasma HIV-1 RNA (copies/mL)			<0.0001
	Median (IQR)	109,900 (30,550 to 327,000)	75,000 (19,800 to 230,000)
	≥500,000	88 (15%)	6,131 (11%)
	100,000-499,999	175 (30%)	14,568 (26%)
	10,000-99,999	181 (31%)	19,000 (34%)
	501-9,999	51 (9%)	7,117 (13%)
	≤ 500	2 (0.3%)	490 (1%)
	Missing	86 (15%)	8,416 (15%)
	NHL, Non Hodgkin Lymphoma; PBL, Primary Brain Lymphoma; KS, Kaposi Sarcoma; baseline relates to
	the first examination after 1.1.1998. P-values from chi-squared tests.

Table 2 :

 2 Incidence rate of systemic non-Hodgkin lymphoma overall and stratified by potential risk factors

			Not on cART			On cART
		No. of NHL	Person-years at risk	Incidence rate per 100,000 person-years (95% CI)	No. of NHL	Person-years at risk	Incidence rate per 100,000 person-years (95% CI)
	All	155	33,503	462.6 (395.3 to 541.5)	366	178,475	205.1 (185.1 to 227.2)
	Age (years)
	16-29	23	8,436	272.6 (181.2 to 410.3)	28	33,163	84.4 (58.3 to 122.3)
	30-39	53	16,091	329.4 (251.6 to 431.2)	159	85,139	186.8 (159.9 to 218.2)
	40-49	48	6,358	754.9 (568.9 to 1,001.8)	100	39,550	252.8 (207.8 to 307.6)
	≥ 50	31	2,618	1,183.9 (832.6 to 1,683.5)	79	20,622	383.1 (307.3 to 477.6)
	Sex
	Women	31	9,759	317.6 (223.4 to 451.7)	64	48,389	132.3 (103.5 to 169.0)
	Men	124	23,743	522.3 (438.0 to 622.8)	302	130,085	232.2 (207.4 to 259.9)
	Transmission risk group
	Injection-drug use	22	7,029	313.0 (206.1 to 475.3)	63	34,850	180.8 (141.2 to 231.4)
	MSM	65	12,103	537.0 (421.1 to 684.8)	149	57,575	258.8 (220.4 to 303.9)
	Heterosexual	49	11,641	420.9 (318.1 to 556.9)	121	70,274	172.2 (144.1 to 205.8)
	Other / unknown	19	2,730	696.1 (444.0 to 1,091.3)	33	15,776	209.2 (148.7 to 294.2)
	CDC clinical stage
	Stage A/B	136	31,517	431.5 (364.8 to 510.5)	271	144,738	187.2 (166.2 to 210.9)
	Stage C without KS	16	1,819	879.7 (538.9 to 1,435.9)	73	29,752	245.4 (195.1 to 308.6)
	Stage C with KS	3	167	1,797.4 (579.7 to 5,573.0)	22	3,985	552.1 (363.5 to 838.5)
	Nadir CD4 count (cells/µ L)
	< 50	29	2,576	1,125.9 (782.4 to 1,620.2)	100	31,338	319.1 (262.3 to 388.2)
	50-99	31	2,572	1,205.4 (847.7 to 1,714.0)	65	19,821	327.9 (257.2 to 418.2)
	100-199	32	9,193	348.1 (246.2 to 492.2)	101	37,866	266.7 (219.5 to 324.2)
	200-349	40	13,948	286.8 (210.4 to 391.0)	73	49,849	146.4 (116.4 to 184.2)
	≥ 350	23	5,214	441.1 (293.1 to 663.8)	27	39,601	68.2 (46.8 to 99.4)
	HIV-1 RNA (copies/mL)
	≥ 500,000	15	1,044	1,436.9 (866.2 to 2,383.4)	68	21,085	322.5 (254.3 to 409.0)
	100,000-499,999	42	4,163	1,009.0 (745.6 to 1,365.3)	119	51,190	232.5 (194.2 to 278.2)
	10,000-99,999	51	12,789	398.8 (303.1 to 524.7)	99	61,130	161.9 (133.0 to 197.2)
	501-9,999	23	9,253	248.6 (165.2 to 374.1)	26	18,595	139.8 (95.2 to 205.4)
	≤ 500	0	-	-	7	3,502	199.9 (95.3 to 419.3)
	cART, combination antiretroviral therapy; NHL, Non Hodgkin Lymphoma; KS Kaposi Sarcoma. Incidence rates from Poisson
	regression models.

Table 3 :

 3 Adjusted hazard ratios for systemic non-Hodgkin lymphoma from multivariable models

		Not on cART	On cART
		Adjusted HR (95% CI)	Adjusted HR (95% CI)
	Age at start cART (years)
	16-29	1	1
	30-39	0.97 (0.59 to 1.61)	1.98 (1.31 to 2.99)
	40-49	1.94 (1.16 to 3.25)	2.35 (1.52 to 3.62)
	≥ 50	2.84 (1.61 to 4.99)	3.72 (2.38 to 5.82)
	Sex
	Women	1	1
	Men	1.12 (0.70 to 1.80)	1.17 (0.86 to 1.59)
	Transmission risk group
	Injection-drug use	0.82 (0.45 to 1.48)	1.10 (0.77 to 1.55)
	MSM	1.23 (0.79 to 1.92)	1.57 (1.19 to 2.08)
	Heterosexual	1	1
	Other/unknown	1.49 (0.85 to 2.63)	1.01 (0.67 to 1.51)
	CDC clinical stage
	Stage A/B	1	1
	Stage C without KS	0.78 (0.43 to 1.43)	0.86 (0.65 to 1.13)
	Stage C with KS	1.00 (0.24 to 4.14)	1.70 (1.08 to 2.68)
	CD4 count (cells/µL)
	< 50	1.15 (0.53 to 2.48)	1.76 (1.20 to 2.58)
	50-99	2.72 (1.46 to 5.04)	1.48 (1.02 to 2.15)
	100-199	1	1
	200-349	0.70 (0.41 to 1.22)	0.60 (0.44 to 0.81)
	≥ 350	0.42 (0.24 to 0.74)	0.30 (0.22 to 0.42)
	HIV-1 RNA (copies/mL)
	≥ 500,000	2.16 (1.21 to 3.87)	1.55 (0.96 to 2.49)
	100,000-499,999	1.75 (1.16 to 2.65)	0.99 (0.66 to 1.48)
	10,000-99,999	1	1
	501-9,999	1.05 (0.64 to 1.72)	1.11 (0.77 to 1.60)
	≤ 500	-	0.60 (0.44 to 0.83)
	HR, hazard ratio; CI, confidence interval; cART, combination antiretroviral therapy; KS Kaposi Sarcoma.
	Models included CD4 count and HIV-1 RNA as time-updated variables and age, sex, transmission risk group
	and CDC clinical stage at baseline or start cART.

Table 4 :

 4 Characteristics of patients with systemic non-Hodgkin lymphoma on cART and not on cART at diagnosis

	Not on cART	On cART	P

Excluded: 958 aged < 16 years at start of observation

	950 without NHL	8 with NHL
		(4 cART naïve, 4 on cART at diagnosis)
	66,701 patients
	Excluded: 1
	56,331 patients
	56,305 patients included in analysis
	55,722 without NHL	583 with NHL
		(174 cART naïve, 409 on cART at diagnosis)

,174 without CD4 cell count after 01.01.1998

	1,155 without NHL	19 with NHL
		(14 cART naïve, 5 on cART at diagnosis)

Excluded: 26 patients in small cohorts with no NHL cases

	65,527 patients
	Excluded: 9
	26 without NHL	0 with NHL

,196 without observation time between 01.01.1998 and start cART or NHL diagnosis

	8,630 without NHL	566 with NHL
		(467 cART naïve, 99 on cART at diagnosis)

Acknowledgements

We are grateful to all patients, doctors and study nurses who were involved in the participating cohorts. This project was funded by a Swiss Bridge Award to Matthias Egger. The COHERE study group is funded by grants from the French Agence Nationale de Recherches sur le Sida et les Hépatites Virales (ANRS), the Dutch HIV Monitoring Foundation and the Danish Augustinus Foundation.

The study was supported in part by the Spanish Network for AIDS Research (RIS; ISCIII-RETIC RD06/006).

Appendix: The Collaboration of Observational HIV Epidemiological Research Europe (COHERE) study group

Writing group for the study of lymphoma Julia Bohlius, 1 Kurt Schmidlin, 1 Dominique Costagliola, 2 Gerd Fätkenheuer, 3 Margaret May, 4 Ana Maria Caro-Murillo, 5 Amanda Mocroft, 6 Fabrice Bonnet, 7 Gary Clifford, 8 Anastasia Karafoulidou, 9 Jose M. Miro, 10 Jens Lundgren, 11 Genevieve Chene, 12 Matthias Egger.


Amandine Viau

Frank Bienaimé

Kamile Lukas

Abhijeet P Todkar

Manuel Knoll

Toma A Yakulov

Alexis Hofherr

Oliver Kretz

Martin Helmstädter

Wilfried Reichardt

Simone Braeg

Tom Aschman

Annette Merkle

Dietmar Pfeifer

Verónica I Dumit

Marie-Claire Gubler

Roland Nitschke

Tobias B Huber

Fabiola Terzi

Jörn Dengjel

Florian Grahammer

Michael Köttgen

Hauke Busch

Melanie Boerries

Gerd Walz

Antigoni Triantafyllopoulou

MD E Wolfgang Kuehn

Cilia-localized LKB 1 regulates chemokine signaling, macrophage recruitment, and tissue homeostasis in the kidney

Keywords: Cilia, macrophages, polycystic kidney disease, nephronophthisis

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Polycystic renal diseases belong to a spectrum of inherited disorders termed ciliopathies. They include genetically distinct and morphologically heterogeneous disorders that manifest at any time from early childhood to late in life and lead to end stage kidney disease in the majority of cases [START_REF] Braun | Ciliopathies. Cold Spring Harbor perspectives in biology[END_REF]. In adults they present as autosomal dominant polycystic kidney disease (ADPKD), one of the most common monogenetic disorders in man, with large numbers of cysts leading to massive enlargement of the kidneys [START_REF] Ong | Autosomal dominant polycystic kidney disease: the changing face of clinical management[END_REF]. In children, the most prevalent form is nephronophthisis (NPHP). These kidneys are mostly small and fibrotic and contain only few cysts [START_REF] Konig | Phenotypic Spectrum of Children with Nephronophthisis and Related Ciliopathies[END_REF][START_REF] Wolf | Nephronophthisis and related syndromes[END_REF]. Important progress has been made in identifying the genetic causes of these entities: ADPKD is caused by mutations in either PKD1 or -2 (1995; [START_REF] Mochizuki | PKD2, a gene for polycystic kidney disease that encodes an integral membrane protein[END_REF]. The number of NPHP genes has surpassed 20 and is growing annually [START_REF] Braun | Ciliopathies. Cold Spring Harbor perspectives in biology[END_REF][START_REF] Hildebrandt | A novel gene encoding an SH3 domain protein is mutated in nephronophthisis type 1[END_REF][START_REF] Saunier | A novel gene that encodes a protein with a putative src homology 3 domain is a candidate gene for familial juvenile nephronophthisis[END_REF]).

Yet, very few insights exist into what links these diverse genes to the disease manifestations of cysts, inflammation and fibrosis.

A key to this question lies in cilia, cell organelles that contain proteins mutated in the ciliopathies. Apart from kidney disease, ciliopathies also affect the liver, the central nervous system and the skeleton [START_REF] Hildebrandt | Ciliopathies[END_REF]. Motile cilia occur in bundles in the airways and brain, whereas primary cilia are non-motile filiform structures at the surface of most cell types, including renal tubules [START_REF] Drummond | Cilia functions in development[END_REF]. Cilia contain a microtubule based cytoskeleton, an ultrastructural gate and a complex macromolecular transport system [START_REF] Garcia-Gonzalo | Open Sesame: How Transition Fibers and the Transition Zone Control Ciliary Composition[END_REF][START_REF] Nachury | How do cilia organize signalling cascades? Philosophical transactions of the Royal Society of London Series B[END_REF][START_REF] Stepanek | Microtubule doublets are double-track railways for intraflagellar transport trains[END_REF]. They act as signal transducers receiving physical and chemical stimuli (Boehlke et al, 2010b;[START_REF] Corbit | Vertebrate Smoothened functions at the primary cilium[END_REF][START_REF] Lechtreck | The Chlamydomonas reinhardtii BBSome is an IFT cargo required for export of specific signaling proteins from flagella[END_REF][START_REF] Praetorius | Bending the MDCK cell primary cilium increases intracellular calcium[END_REF] and affect a wide range of autonomous cellular functions such as cell size, polarity, cell cycle and migration (Boehlke et al, 2010b;[START_REF] Jones | Ciliary proteins link basal body polarization to planar cell polarity regulation[END_REF][START_REF] Kim | The Bardet-Biedl protein BBS4 targets cargo to the pericentriolar region and is required for microtubule anchoring and cell cycle progression[END_REF][START_REF] Orhon | Primary-ciliumdependent autophagy controls epithelial cell volume in response to fluid flow[END_REF][START_REF] Park | Ciliogenesis defects in embryos lacking inturned or fuzzy function are associated with failure of planar cell polarity and Hedgehog signaling[END_REF][START_REF] Robert | The intraflagellar transport component IFT88/polaris is a centrosomal protein regulating G1-S transition in non-ciliated cells[END_REF][START_REF] Schneider | Directional cell migration and chemotaxis in wound healing response to PDGF-AA are coordinated by the primary cilium in fibroblasts[END_REF][START_REF] Vasilyev | Collective cell migration drives morphogenesis of the kidney nephron[END_REF]. However, it is unclear how the dysfunction of cilia explains the phenotype of renal ciliopathies.

When exploring this question two observations prompted our attention. First, apart from cysts ADPKD and NPHP share an inflammatory phenotype: in NPHP inflammation and subsequent fibrosis are much more prominent than cysts [START_REF] Braun | Ciliopathies. Cold Spring Harbor perspectives in biology[END_REF][START_REF] Hildebrandt | A novel gene encoding an SH3 domain protein is mutated in nephronophthisis type 1[END_REF][START_REF] Saunier | A novel gene that encodes a protein with a putative src homology 3 domain is a candidate gene for familial juvenile nephronophthisis[END_REF][START_REF] Slaats | Nephronophthisis: should we target cysts or fibrosis?[END_REF][START_REF] Wolf | Nephronophthisis and related syndromes[END_REF]. Likewise, in ADPKD macrophage infiltration occurs early on and promotes cyst enlargement [START_REF] Karihaloo | Macrophages promote cyst growth in polycystic kidney disease[END_REF]. Similarly to NPHP, the late stages of ADPKD are characterized by a severe degree of fibrosis [START_REF] Norman | Fibrosis and progression of autosomal dominant polycystic kidney disease (ADPKD)[END_REF][START_REF] Ong | Autosomal dominant polycystic kidney disease: the changing face of clinical management[END_REF]. The second aspect concerns the fact that metabolic signalling has been observed to contribute to ADPKD and NPHP [START_REF] Chaki | Exome capture reveals ZNF423 and CEP164 mutations, linking renal ciliopathies to DNA damage response signaling[END_REF][START_REF] Menezes | Fatty Acid Oxidation is Impaired in An Orthologous Mouse Model of Autosomal Dominant Polycystic Kidney Disease[END_REF][START_REF] Rowe | Defective glucose metabolism in polycystic kidney disease identifies a new therapeutic strategy[END_REF]. We therefore asked the question how cilia, metabolic signal transducers and inflammation are linked.

An interesting candidate to explore this question is the kinase LKB1 (liver kinase B1). LKB1 is a metabolic sensor localized in cilia (Boehlke et al, 2010b;[START_REF] Mick | Proteomics of Primary Cilia by Proximity Labeling[END_REF].

We have previously shown in vitro, that bending of cilia under flow activates LKB1 to phosphorylate its target AMPK (5' adenosine monophosphate-activated protein kinase) at the base of cilia and to regulate metabolic signalling linked to PKD (Boehlke et al, 2010b;[START_REF] Liu | Sirolimus for treatment of autosomal-dominant polycystic kidney disease: a meta-analysis of randomized controlled trials[END_REF][START_REF] Orhon | Primary-ciliumdependent autophagy controls epithelial cell volume in response to fluid flow[END_REF][START_REF] Walz | Everolimus in patients with autosomal dominant polycystic kidney disease[END_REF]. To explore the role of LKB1 in vivo we inactivated LKB1 in the kidney. First, we asked if renal deletion of LKB1 induces a renal ciliopathy phenotype. Second, we sought to uncover molecular mechanisms connecting LKB1, cilia, and PKD proteins to cysts, inflammation and fibrosis.

Results

Deletion of LKB1 in the kidney disrupts renal morphology and function

Mono-allelic mutations in the gene STK11/LKB1 in humans cause Peutz-Jeghers disease, an inherited cancer syndrome characterized by benign tumors of the skin and intestine, as well as the development of malignancies [START_REF] Hemminki | A serine/threonine kinase gene defective in Peutz-Jeghers syndrome[END_REF]. Lkb1 -/-mice display severe developmental defects leading to embryonic lethality. We therefore pursued a kidney specific knock-out strategy and crossed Lkb1 flox/flox mice [START_REF] Nakada | Lkb1 regulates cell cycle and energy metabolism in haematopoietic stem cells[END_REF] with a kidney specific deleter strain to excise Lkb1 in the distal nephron. LKB1 was absent from the cilia of these tubule segments (Lkb1 ΔTub Loss of LKB1 in the kidney results in alterations of tubular architecture, cysts, and chronic inflammation with progressive scarring leading to renal failure, reminiscent of a renal ciliopathy phenotype.

LKB1 interacts with ciliopathy proteins and a functional interaction exists between

LKB1 and NPHP1

To obtain insights into what might explain the phenotype of LKB1 deletion in the kidney, we performed a proteomic screen in protein lysates from renal medulla, aiming to identify endogenous interactors of LKB1 that might illuminate its function. The LKB1 precipitates obtained from these lysates were highly enriched for the known LKB1 interactor STRADa and 30 other proteins (Fig 2A and Dataset EV1,2). Of these, 12 have previously been implicated in renal physiology or development (Dataset EV1). Two of them have been linked to the renal ciliopathy nephronophthisis (NPHP): ANKS3 (ankyrin repeat and sterile alpha motif domain containing 3) and NEK7 (NIMA (never in mitosis gene a)-related kinase 7). ANKS3 is a ciliopathy protein and a known interactor of several proteins involved in NPHP, including NPHP1 [START_REF] Leettola | Characterization of the SAM domain of the PKD-related protein ANKS6 and its interaction with ANKS3[END_REF][START_REF] Shamseldin | ANKS3 is mutated in a family with autosomal recessive laterality defect. Human genetics Shao X, Somlo S, Igarashi P[END_REF][START_REF] Yakulov | Anks3 interacts with nephronophthisis proteins and is required for normal renal development[END_REF], the protein mutated in 60% of patients with genetically defined NPHP [START_REF] Halbritter | Identification of 99 novel mutations in a worldwide cohort of 1,056 patients with a nephronophthisis-related ciliopathy[END_REF][START_REF] Hildebrandt | A novel gene encoding an SH3 domain protein is mutated in nephronophthisis type 1[END_REF][START_REF] Konig | Phenotypic Spectrum of Children with Nephronophthisis and Related Ciliopathies[END_REF][START_REF] Saunier | A novel gene that encodes a protein with a putative src homology 3 domain is a candidate gene for familial juvenile nephronophthisis[END_REF].

ANKS3 also has a physical and functional interaction with NEK7 and NEK7 is part of the cilia proteome [START_REF] Mick | Proteomics of Primary Cilia by Proximity Labeling[END_REF][START_REF] Ramachandran | Anks3 alters the sub-cellular localization of the Nek7 kinase[END_REF]. We confirmed the endogenous interaction between LKB1, ANKS3 and NEK7 by co-immunoprecipitations from renal medulla (Fig 2B) and found that ANKS3 localizes to cilia .

The interaction between LKB1 and two cilia proteins associated with NPHP1 is interesting, since the phenotype of the Lkb1 ΔTub mice resembles NPHP in children.

Furthermore, it suggests a functional synergy between LKB1 and NPHP1. Indeed, LKB1 co-immunoprecipitated with NPHP1 (Fig 2F and Fig EV2A), but interacted only weakly with NPHP2, -3, -4, and -8 (Fig EV2B ,C). To test if LKB1 and NPHP1 have a functional interaction we used zebrafish, an established model for ciliopathy phenotypes [START_REF] Kramer-Zucker | Cilia-driven fluid flow in the zebrafish pronephros, brain and Kupffer's vesicle is required for normal organogenesis[END_REF][START_REF] Tuz | Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK Prospective Diabetes Study (UKPDS) Group[END_REF]. Morpholino-mediated knock-down of NPHP proteins and anks3 in zebrafish larvae results in the formation of pronephric cysts [START_REF] Yakulov | Anks3 interacts with nephronophthisis proteins and is required for normal renal development[END_REF]. We found that knock-down of nphp1 caused cyst formation in a minority of larvae, whereas knock-down of lkb1 alone had no effect (Fig 2G ,H). However, co-injection of both morpholinos strongly increased the proportion of larvae with a cystic phenotype (Fig 2H). Taken together, these findings link LKB1 and NPHP1 in physical and functional terms. They suggest that LKB1 is in a complex with NPHP1, ANKS3, and NEK7, and open the possibility that this module regulates signalling events downstream of cilia relevant to the observed renal phenotype.

Loss of LKB1 results in epithelial upregulation of CCL2 and is associated with the accumulation of CCR2 + macrophages.

We were interested in the downstream events explaining the inflammation and fibrosis in Lkb1 ΔTub kidneys. The best characterized target of LKB1 signalling is the AMP sensing kinase AMPK but other downstream substrates are known [START_REF] Lizcano | LKB1 is a master kinase that activates 13 kinases of the AMPK subfamily, including MARK/PAR-1[END_REF][START_REF] Shaw | The tumor suppressor LKB1 kinase directly activates AMP-activated kinase and regulates apoptosis in response to energy stress[END_REF]. LKB1 phosphorylates AMPK to inhibit mTORC1 and protein synthesis.

We did not find consistent signals demonstrating dysregulation of AMPK or mTORC1 signalling in the tubules of Lkb1 ΔTub kidneys (Appendix Fig. S2), suggesting that alternative signalling events triggered by LKB1 inactivation are involved in the renal pathology. To approach this issue in an unbiased fashion we performed microarray analysis in Lkb1 mutant kidneys at an early time point, when there was only little damage to the parenchyma (Fig 1F,5 weeks). We compared these data with RNA seq analyses performed in MDCK cells where Lkb1 was depleted by shRNA induced knock-down (Boehlke et al, 2010b) (Fig 3A, Fig EV3A, B and Dataset EV3). This approach allowed us to discard regulated transcripts from the kidney that came from outside renal epithelia. At the same time, it enabled us to look at transcripts that we might have discarded, if we had assumed that they originate in non-epithelial cells, for instance immune cells. Network analysis of clustered GO terms for the 99 commonly upregulated genes revealed changes in biological processes relating to organ development, morphogenesis and angiogenesis which are in keeping with the role of LKB1 in early development and cancer (Fig EV3C and Dataset EV4), while the 41 downregulated genes represented mostly metabolic processes (Dataset EV5). Surprisingly, the upregulated genes revealed clusters incorporating immune response, cytokine production and immune cell migration (Fig EV3C). The two most highly upregulated genes in the renal tubular cell derived set that were co-regulated in vivo were the cytokine inducible transcription factor ANKRD1 (Ankyrin repeat domain 1) and the inducible cytokine CCL2 (chemokine (C-C motif) ligand 2) (Fig 3B and Dataset EV3). CCL2 (also known as Monocyte Chemoattractant Protein 1 or MCP1), is a potent chemoattractant of bone marrow derived CCR2 + blood monocytes which are critical progenitors for tissue macrophages in many pathological conditions, including bacterial immunity, tumors and inflammation [START_REF] Cao | Macrophages in kidney injury, inflammation, and fibrosis[END_REF][START_REF] Franklin | The cellular and molecular origin of tumor-associated macrophages[END_REF][START_REF] Serbina | Monocyte emigration from bone marrow during bacterial infection requires signals mediated by chemokine receptor CCR2[END_REF]. As CCL2 has been shown to promote macrophage recruitment and disease progression in chronic kidney disease [START_REF] Cao | Macrophages in kidney injury, inflammation, and fibrosis[END_REF], we focused our attention on this protein. CCL2 upregulation was confirmed in Lkb1 mutant kidneys as well as in cells after shRNA mediated depletion of LKB1 and was prevented by AICAR treatment Fig EV3D,E and Appendix Fig S3). These data identify CCL2 as a highly upregulated chemokine in the kidney after loss of LKB1 in vivo. Our in vitro data demonstrate that renal tubular cells are the source of CCL2 in LKB1 deficiency.

To better characterize the local inflammatory response triggered by inactivation of Lkb1 in vivo we analyzed renal cell suspensions from Lkb1 mutant mice and littermate controls by flow cytometry (Triantafyllopoulou et al, 2010) (Appendix Fig S5): Lkb1 mutant mice contained significantly increased numbers of CD45-positive leukocytes. This was in part explained by increased numbers of neutrophils, while B and T cell numbers were not significantly changed. Strikingly, kidney monocytes and CD11b hi macrophages expressing CCR2, the CCL2 receptor, were significantly increased . These findings support the notion that LKB1 deficient renal epithelial cells in the kidney take on an inflammatory phenotype and release CCL2, resulting in the recruitment of mononuclear phagocytes and macrophage activation.

The LKB1/NPHP1/ANKS3/NEK7 complex controls CCL2 expression

The data described above raise two questions: (1) does the complex of LKB1 with NPHP1, ANKS3 and NEK7 regulate CCL2? (2) If so, does this regulation require cilia? To address the first question we resorted to a loss of function approach using shRNA mediated knock-down in cultured renal epithelial cells. Remarkably, depletion of NPHP1 but not NPHP4 resulted in upregulation of Ccl2 in MDCK cells (Fig 5A and Appendix Fig S3). Similar to the findings in NPHP1 or LKB1 knock-down cells, Ccl2 was increased in cells depleted of ANKS3 or NEK7 while total LKB1 expression was not affected (Fig 5B,Fig EV2F,G and Appendix Fig S3 and S4). This indicates that LKB1, NPHP1, ANKS3, and NEK7 act as a signalling module to suppress this chemokine.

The ciliary isoform of the LKB1 interactor STRAD is required for CCL2 regulation.

LKB1, in addition to the cilium, resides in the nucleus and the cytosol. To clarify if the LKB1 module acts in cilia, we sought evidence that ciliary localization of LKB1 is required for suppression of CCL2. To address this question we focused on the functional LKB1 interactors STRADa and -b [START_REF] Zeqiraj | Structure of the LKB1-STRAD-MO25 complex reveals an allosteric mechanism of kinase activation[END_REF] which are part of a hetero-trimeric complex and required for the kinase activity of LKB1 [START_REF] Baas | Activation of the tumour suppressor kinase LKB1 by the STE20-like pseudokinase STRAD[END_REF][START_REF] Boudeau | MO25alpha/beta interact with STRADalpha/beta enhancing their ability to bind, activate and localize LKB1 in the cytoplasm[END_REF]. Indeed, we found that NPHP1 interacts with STRAD, supporting a functional role of the LKB1-NPHP1 interaction (Fig EV2D ). STRADb has been reported to mediate entry of LKB1 into cilia whereas STRADa is required for LKB1 function in the cytosol [START_REF] Boudeau | MO25alpha/beta interact with STRADalpha/beta enhancing their ability to bind, activate and localize LKB1 in the cytoplasm[END_REF][START_REF] Mick | Proteomics of Primary Cilia by Proximity Labeling[END_REF]. Indeed, we found that tagged versions of STRADb, but not Notably, depletion of STRADb recapitulated the Ccl2 increase seen after LKB1 or NPHP1 depletion, whereas this was not the case for knock-down of STRADa (Fig 5F and Appendix Fig S3). Since STRADb is the functional interactor of LKB1 within the cilium, these data confirm that LKB1 is required within cilia to regulate CCL2.

Primary cilia are positive regulators of CCL2

At this point our findings suggested two possible alternatives of how cilia might regulate CCL2. They could either act as negative regulators of CCL2, in which case removal of cilia would increase expression of CCL2. Or they could act as sensors of a CCL2 inducing signal that is negatively regulated by the LKB1 module, in which case removal of the cilium would decrease CCL2 levels. A similar mechanism has been described for hedgehog, a developmental pathway that processes crucial signalling steps within cilia [START_REF] Bangs | Primary Cilia and Mammalian Hedgehog Signaling[END_REF][START_REF] Corbit | Vertebrate Smoothened functions at the primary cilium[END_REF]. Indeed, we found the second possibility to be the case. We ablated cilia by interfering with intraflagellar transport (IFT).

Targeting the ciliary kinesin subunit KIF3a or the IFT protein IFT88 prevents cells from forming cilia (Boehlke et al, 2010b;[START_REF] Marszalek | Situs inversus and embryonic ciliary morphogenesis defects in mouse mutants lacking the KIF3A subunit of kinesin-II[END_REF][START_REF] Pazour | Chlamydomonas IFT88 and its mouse homologue, polycystic kidney disease gene tg737, are required for assembly of cilia and flagella[END_REF]. We found that cilia deficient compared to ciliated cells expressed lower levels of Ccl2 (Fig 5G and Appendix Fig S3). Furthermore, co-ablation of cilia together with LKB1 prevented the increase of Ccl2 that is seen after LKB1 depletion alone (Fig 5H and Appendix Fig S3) suggesting that cilia are required for the up-regulation of CCL2 and that the LKB1 module inhibits cilia induced CCL2 expression (Fig 8A ,B).

PKD1 interacts with LKB1 and STRAD

A cilia dependent cyst activating mechanism has been postulated for the ciliopathy ADPKD [START_REF] Ma | Loss of cilia suppresses cyst growth in genetic models of autosomal dominant polycystic kidney disease[END_REF]. This mechanism is inhibited by PKD1 under physiological conditions and is released in the presence of a PKD mutation, driving cyst growth.

However, the putative ciliary downstream signal has not been identified. We therefore wondered if deregulated CCL2 control by dysfunction of the LKB1 module in cilia plays a role in ADPKD. Consistent with this notion, we found that PKD1 co-immunoprecipitates with LKB1 and both . Furthermore, analysing PKD1 null renal epithelial cells that were constructed using TALEN-based genome editing (Appendix Fig S3) [START_REF] Hofherr | Efficient genome editing of differentiated renal epithelial cells[END_REF], we observed that Ccl2 was upregulated compared to wild type that PKD1 is required for LKB1 to repress Ccl2 expression. Taken together, these findings, obtained in vitro in a cell based system, demonstrate that a physical and functional interaction exists between PKD1 and the LKB1 module. Our findings suggest that PKD1 and the LKB1 module form a functional unit to inhibit a ciliary CCL2 inducing signal and that PKD1 is required for its function. This raised the possibility that deregulation of CCL2 may play a role in the pathological changes occurring in ADPKD.

Cilia induced CCL2 promotes disease progression in a mouse model of ADPKD

Inflammation and fibrosis lead to a loss of parenchyma and small kidneys in patients with NPHP [START_REF] Konig | Phenotypic Spectrum of Children with Nephronophthisis and Related Ciliopathies[END_REF]. In ADPKD, however, macrophages have been shown to be activators of cyst growth, thus leading to kidney enlargement and disease progression [START_REF] Karihaloo | Macrophages promote cyst growth in polycystic kidney disease[END_REF], providing a rationale for the hypothesis that the regulatory effect of PKD1 and LKB1 on cilia induced CCL2 expression is relevant for human pathology. We tested this hypothesis in an orthologous model of ADPKD, where postnatal inactivation of Pkd1 results in slow onset PKD, recapitulating human disease (Ma et al, 2013) (Fig 6E, F and Fig EV4). In these kidneys, we observed that an early stage of cyst formation was accompanied by the up-regulation of Ccl2 transcript but no change in LKB1 or other members of the regulatory complex (Fig 6G and Appendix Fig S4). Flow cytometry analysis revealed that CCR2 + kidney mononuclear phagocytes were markedly increased in Pkd1 deficient kidneys (Fig 6H -K). In contrast, kidney B and T lymphocytes and neutrophils were not significantly increased at this early time point (Appendix Fig S6).

To test if cilia are required for the upregulation of CCL2 in Pkd1 deficient kidneys, we generated mice with simultaneous targeting of Pkd1 and Kif3a. As has been described [START_REF] Ma | Loss of cilia suppresses cyst growth in genetic models of autosomal dominant polycystic kidney disease[END_REF]

Discussion

We define here that cilia of renal tubules actively regulate peri-tubular macrophage numbers. Cilia act as signal transducers to increase expression of the chemokine CCL2.

The signal inducing CCL2 is regulated by a ciliary module involving LKB1, the cililopathy proteins NPHP1, PKD1, and ANKS3, as well as NEK7. Genetic targeting of Lkb1 or Pkd1 in the kidney in vivo results in mononuclear phagocyte recruitment and the promotion of ciliopathy phenotypes. Ablation of cilia or CCL2 in Pkd1 mutant mice prevents this pathophysiology and ameliorates the disease.

The loss of LKB1 in kidney tubules leads to a progressive disruption of renal architecture and function resembling a nephronophthisis phenotype. These events are characterized by inflammation and fibrosis, and involve the secretion of CCL2 and expansion of CCR2 + macrophages. LKB1 regulates CCL2 by interacting with three proteins linked to NPHP, a ciliopathy occurring in children and adolescents. Among them is NPHP1, the protein most commonly mutated in genetically defined NPHP, and two interacting cilia proteins: ANKS3 and NEK7, the first of which is a ciliopathy protein itself.

All of these proteins are required for CCL2 regulation.

The LKB1 regulatory module acts within cilia: LKB1 exerts its CCL2 suppressive function only in the presence of the cilia specific LKB1 interactor STRADb, but not in its absence when only the cytosolic STRADa is present. In the absence of cilia CCL2 does not increase, suggesting that cilia carry a positive signal regulating CCL2 which is blocked by the LKB1 module. This is supported in vivo by the finding that ablation of cilia or CCL2 together with PKD1 ameliorates the cystic phenotype in a similar manner.

Our findings suggest that this mechanism is relevant for the human ciliopathy ADPKD. Based on observations in orthologous mouse models that ablation of cilia ameliorates the ADPKD phenotype, it has been proposed that PKD1 blocks a cilia dependent cyst activating signal whose nature has not been specified [START_REF] Ma | Loss of cilia suppresses cyst growth in genetic models of autosomal dominant polycystic kidney disease[END_REF]. Indeed, CCL2 is such a signal: We find that PKD1 interacts with LKB1 and its functional interactor STRAD. Loss of PKD1 in vitro and in vivo stimulates CCL2 expression in a cilia dependent way: In a PKD1 mouse model we find that lack of cilia results in lower amounts of CCR2 + macrophages and decreased cyst formation. In addition, deletion of CCL2 concomitant with PKD1 in renal tubules reduces macrophage numbers and ameliorates cyst formation. These findings are consistent with previously published data showing that macrophage recruitment is a driving force for cyst growth in different animal models of PKD [START_REF] Chen | Macrophage migration inhibitory factor promotes cyst growth in polycystic kidney disease[END_REF][START_REF] Cowley | Increased renal expression of monocyte chemoattractant protein-1 and osteopontin in ADPKD in rats[END_REF][START_REF] Karihaloo | Macrophages promote cyst growth in polycystic kidney disease[END_REF][START_REF] Norman | Fibrosis and progression of autosomal dominant polycystic kidney disease (ADPKD)[END_REF][START_REF] Puri | Six2creFrs2alpha knockout mice are a novel model of renal cystogenesis[END_REF]. Indeed, in human patients CCL2 excretion in the urine has been found to be a marker of ADPKD disease progression [START_REF] Zheng | Urinary excretion of monocyte chemoattractant protein-1 in autosomal dominant Figure EV2. Immunoprecipitation experiments (IP) from HEK 293T cells A. FLAG-LKB1 is enriched in the precipitates of V5.NPHP1 and V5.STRADa, but not V5.GFP. B, C. Endogenous LKB1 is enriched in the precipitates of FLAG-(B) or V5-tagged (C) NPHP1 but interacts weakly with[END_REF] suggesting that the regulation of CCL2 by the ciliary LKB1 module is clinically important.

Could there also be a wider role for ciliary LKB1 in renal disease? Inflammation and fibrosis represent a final common pathway in different types of chronic renal disease [START_REF] Cao | Macrophages in kidney injury, inflammation, and fibrosis[END_REF], but in a large number of cases the inflammatory trigger is not established. In the German chronic kidney disease cohort, with over 5000 participants, less than one third of the patients had an underlying chronic inflammatory disorder such as autoimmune disease [START_REF] Titze | Disease burden and risk profile in referred patients with moderate chronic kidney disease: composition of the German Chronic Kidney Disease (GCKD) cohort. Nephrology, dialysis, transplantation[END_REF]. Among the remaining patients the causes were diabetes (15%) vascular (25%) or undetermined (21%). Both, diabetes and vascular disease are metabolic disorders. Of note, LKB1 is a metabolic sensor and CCL2 signalling has been implicated in diabetic kidneys and vascular disease [START_REF] Bot | A novel CCR2 antagonist inhibits atherogenesis in apoE deficient mice by achieving high receptor occupancy[END_REF][START_REF] Sayyed | An orally active chemokine receptor CCR2 antagonist prevents glomerulosclerosis and renal failure in type 2 diabetes[END_REF].

This raises the possibility that in metabolic disease the ciliary LKB1 module could confer an inflammatory phenotype on renal epithelial cells to mediate chronic inflammation in the kidney. Given that chronic kidney disease is now the tenth leading cause of death worldwide [START_REF] Eckardt | Evolving importance of kidney disease: from subspecialty to global health burden[END_REF]GBD2015-Collaborators, 2016) this is of considerable interest.

LKB1 might link cilia to inflammation also outside the kidney: Obesity and diabetes are states of energy excess and metformin, an antidiabetic drug that augments the effect of LKB1 on AMPK is particularly effective in obese diabetics (UKPDS-Group, 1998).

Obesity and diabetes are accompanied by low grade inflammation in a positive feedback loop, particularly in adipose tissue, where adipocytes release CCL2 to recruit CCR2 expressing monocytes [START_REF] Brestoff | Immune regulation of metabolic homeostasis in health and disease[END_REF][START_REF] Hotamisligil | Nutrient sensing and inflammation in metabolic diseases[END_REF][START_REF] Weisberg | CCR2 modulates inflammatory and metabolic effects of highfat feeding[END_REF]. Diabetes associated inflammation also occurs in the heart, which similarly to the kidney develops interstitial fibrosis in diabetic subjects [START_REF] Bugger | Molecular mechanisms of diabetic cardiomyopathy[END_REF]. Indeed, it has been shown that LKB1 deletion in the heart promotes fibrosis and heart failure [START_REF] Ikeda | Cardiacspecific deletion of LKB1 leads to hypertrophy and dysfunction[END_REF]. A further setting where the link between LKB1 and inflammation may play a role is malignant disease: Somatic loss of LKB1 occurs in a variety of cancers, particularly cervical and lung cancer, which both carry a poor prognosis [START_REF] Ji | LKB1 modulates lung cancer differentiation and metastasis[END_REF][START_REF] Wingo | Somatic LKB1 mutations promote cervical cancer progression[END_REF]. It is interesting in this respect that CCL2 induced macrophage recruitment has been found to promote metastatic seeding of cancer cells [START_REF] Pena | LKB1 loss promotes endometrial cancer progression via CCL2-dependent macrophage recruitment[END_REF][START_REF] Qian | CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis[END_REF] and that in pancreatic cancer the presence of cilia correlates with more metastases and a worse prognosis [START_REF] Emoto | Presence of primary cilia in cancer cells correlates with prognosis of pancreatic ductal adenocarcinoma[END_REF].

In summary we describe that cilia actively promote chemokine signalling and inflammation in the kidney and that this pathway is suppressed by a module involving LKB1, NPHP associated proteins, and PKD1. Loss of PKD1 activates the pathway and promotes disease progression in an orthologous model of ADPKD.

Materials and Methods

Mice

All animal experiments were conducted according to the guidelines of the National Institutes of Health Guide for the Care and Use of Laboratory Animals, as well as the German law for the welfare of animals, and were approved by regional authorities (Regierungspräsidium Freiburg G-13/18, G-15/58 and G-16/28). Mice were housed in a specific pathogen-free facility, fed ad libitum and housed at constant ambient temperature in a 12-hour day/night cycle. Breeding and genotyping were done according to standard procedures.

Lkb1 flox/flox mice (mixed genetic background) were purchased from The Jackson Laboratories (STOCK Stk11 tm1.1Sjm /J, stock number: 014143) and were crossed to KspCre mice (B6.Cg-Tg(Cdh16-cre)91lgr/J; C57Bl/6N background) (Shao et al, 2002) to generate a tubule-specific Lkb1 knockout (further referred to as Lkb1 Tub ). Lkb1 flox/+ and Lkb1 flox/flox littermates without the KspCre transgene were used as controls. Experiments were conducted on both females and males.

For co-immunoprecipitation studies, C57BL/6J male mice were used from the local stock of the animal facility of Freiburg University.

Pkd1 flox/flox mice (B6.129S4-Pkd1tm2Ggg/J, stock number: 010671, C57BL/6 genetic background) and Ccl2-RFP flox/flox (B6.Cg-Ccl2tm1.1Pame/J, stock number : 016849, C57BL/6 genetic background) were purchased from The Jackson Laboratories, Kif3a flox/flox mice (Kif3atm1Gsn, C57BL/6 genetic background) were kindly provided by Peter Igarashi, and were crossed to Pax8rtTA [START_REF] Traykova-Brauch | An efficient and versatile system for acute and chronic modulation of renal tubular function in transgenic mice[END_REF] and TetOCre [START_REF] Eremina | VEGF inhibition and renal thrombotic microangiopathy[END_REF] mice to generate an inducible tubule-specific Pkd1 knockout (further referred to as iPkd1 Tub ), Pkd1; Ccl2 knockout (further referred to as iPkd1 Tub ; iCcl2 Tub ) and Pkd1; Kif3a knockout (further referred to as iPkd1 Tub ; iKif3a Tub ). From post-natal day 28 (P28) to P42, mice received doxycycline hydrochloride (Fagron) via the drinking water (2mg/mL with 5% sucrose, protected from light) for a period of 14 days. Littermates (lacking either TetOCre or Pax8rtTA) were used as controls. Experiments were conducted on males.

Zebrafish line maintenance and embryo manipulation

Zebrafish strains were maintained and raised as described [START_REF] Epting | The Rac1 regulator ELMO controls basal body migration and docking in multiciliated cells through interaction with Ezrin[END_REF]. Transgenic wt1b::GFP zebrafish embryos [START_REF] Perner | The Wilms tumor genes wt1a and wt1b control different steps during formation of the zebrafish pronephros[END_REF] were injected with 0.5 mM morpholino (MO; Gene Tools LLC) targeting lkb1

(5'-GAGATCCGCGCCCACGCTCATCTTT-3' as described [START_REF] Jacob | Genome-wide RNAi screen reveals disease-associated genes that are common to Hedgehog and Wnt signaling[END_REF])) or nphp1 (5'-CCCTCTTCTCTTTGGAGGCATGTTG-3' as described [START_REF] Slanchev | Nephrocystin-4 is required for pronephric duct-dependent cloaca formation in zebrafish[END_REF])) at the onecell stage. All MOs were co-injected with 0.1mM p53 MO (5'-GCGCCATTGCTTTGCAAGAATTG-3') to reduce the unspecific effects of the reagents.

To correct for the amount of total MO in the combined knockdown experiment, 0.5 mM standard control MO (5'-CCTCTTACCTCAGTTACAATTTATA-3') was simultaneously injected. Embryos were analyzed at 48-50 h.p.f. under a Leica MZ16 stereo microscope (Leica). Images were recorded using a Leica DFC450 C (Leica).

Magnetic resonance imaging (MRI)

MRI was performed on anaesthetised animals at 10 and 16 weeks of age using a 9.4-T (400 MHz) horizontal magnet equipped with a 38mm inner diameter quadrature birdcage coil (Bruker Biospin), as previously described [START_REF] Grahammer | mTORC1 maintains renal tubular homeostasis and is essential in response to ischemic stress[END_REF]. Briefly, anaesthesia was induced with isofluorane, breathing and heart rate were monitored by ECG. Fast imaging technique and cardiac gating were applied to reduce motion artifacts.

A fast spin-echo sequence (TR/TEeff/FA: 4800 ms/36 ms/180•; echo train length, 8) was used to achieve T2 contrast. The sequence featured a 30 × 30 mm field of view, a matrix size of 256 ×256 pixels, and an in-plane resolution of 117 × 117 mm. The slice thickness was 0.5 mm with no slice spacing to achieve contiguous image sets of the whole volume.

Morphological analyses were performed using Medical Image Processing and Visualization (MIPAV) software (National Institutes of Health). To determine the total kidney volume, the perimeter of the kidney, which could be clearly distinguished from the surrounded tissue, was delineated manually on each slice image. The total kidney volume was calculated from sets of contiguous images by summing up the products of area measurements and slice thickness using the volume of interest tool in MIPAV as previously described [START_REF] Grahammer | mTORC1 maintains renal tubular homeostasis and is essential in response to ischemic stress[END_REF].

Urine and Plasma Analyses

8-hour urine samples were obtained from mice housed in individual boxes without access to water and food. Body weight and urine excretion were measured. Urine osmolality was measured with a freezing point depression osmometer (Micro-Osmometer from Knauer or OSMOMAT 3000basic from Gonotec). Retro-orbital blood was collected from anaesthetised mice. Plasma blood urea nitrogen (BUN) was measured using urea kit (LT-UR; Labor&Technik, Eberhard Lehmann GmbH) according to the manufacturer's instructions.

Transmission electron microscopy

Transmission electron microscopy was performed as previously described [START_REF] Grahammer | mTORC1 maintains renal tubular homeostasis and is essential in response to ischemic stress[END_REF]. Briefly, 4% paraformaldehyde perfusion-fixed kidneys were post-fixed in 1% glutaraldehyde/ 4% paraformaldehyde for 24 hours at 4°C. Subsequently, kidneys were post-fixed in 1% osmium tetroxide (Roth) for 1 hour and then with 1% uranyl acetate in 70% EtOH overnight at 4°C (Polysciences), dehydrated and embedded in durcupan resin (Plano). Ultrathin sections were performed using a UC6 ultramicrotome (Leica), collected on formvar (Plano) coated copper grids and imaged using a Phillips CM 100 transmission electron microscope.

Scanning electron microscopy

For scanning electron microscopy, 4% paraformaldehyde perfusion-fixed kidneys were post-fixed in 1% glutaraldehyde/ 4% paraformaldehyde for 24 hours at 4°C and were subsequently dehydrated in ethanol (70-100% -each step for 1h at RT). Deyhydrated kidney samples were then incubated with the solvent HMDS in a 1:1 solution with EtOH for 30 minutes. Final dehydration was then performed in 100% HMDS. Kidney samples were dissected using syringe needles under a binocular microscope. Sputtering with gold was performed using a Polaron Cool Sputter Coater E 5100. Samples were visualized using a scanning electron microscope (Leo 1450 VP scanning).

Morphological Analysis

Mouse kidneys were fixed in 4% paraformaldehyde, embedded in paraffin, and 4µm sections were stained with periodic acid-Schiff (PAS) or Picrosirius Red. PAS stained sections were imaged using an AxioPlan2 (Zeiss) equipped with a Plan Neofluar 20x/0.30 NA objective and an AxioCam camera (Zeiss). PAS stained full size images were recorded using an AxioObserver Z1 (Zeiss) equipped with an EC Plan Neofluar 2.5x/0.085 NA objective and an AxioCam camera (Zeiss) or using a whole slide scanner Nanozoomer 2.0 (Hamamatsu) equipped with a 20x/0.75 NA objective coupled to NDPview software (Hamamatsu). Picrosirius Red stained sections were imaged using an AxioImager Z1

(Zeiss) equipped with a Plan Apochromat 40x/0.95 NA objective and an AxioCam camera (Zeiss). Image recording was performed using AxioVision software (Zeiss) or ZenBlue Software (Zeiss).

Plasmids

Tagged-constructs for CD2AP, GFP, NPHP1, NPHP2, NPHP3, NPHP4, NPHP8

were previously described [START_REF] Hoff | ANKS6 is a central component of a nephronophthisis module linking NEK8 to INVS and NPHP3[END_REF]. Tagged-LKB1 and -STRADa constructs were kindly provided by Andrea Thiele from Hubrecht Lab and Clevers Lab, respectively.

STRADb was cloned from Clone 3549243 (Source BioScience). FLAG.MO25a and -b were cloned from canine cDNA into pcDNA6 in-frame with N-terminal FLAG tag.

FLAG.PKD1 construct was kindly provided by Michael Caplan [START_REF] Grimm | Polycystin-1 distribution is modulated by polycystin-2 expression in mammalian cells[END_REF]. S1.

Cell culture, transfections, co-immunoprecipitation and transgenic cell lines

Human embryonic kidney (HEK 293T) cells (ATCC Promocell; CRL-11268) are listed in the database of commonly misidentified cell lines maintained by ICLAC and NCBI Biosample and were authenticated by Interspecies Determination (Isoenzyme Analysis and STR Analysis) by the providing company. HEK 293T cells were cultured using Dulbecco's Modified Eagle Medium supplemented with 10% fetal bovine serum (Biochrome). Plasmids were transiently transfected using calcium. For coimmunoprecipitation cells were lysed in CHAPS buffer (40mM Hepes pH 7.5, 120mM

NaCl, 1mM EDTA, 0.30% CHAPS) supplemented with 1mM Na3VO4, 50mM NaF, 5mM

-glycerophosphate and protease inhibitor cocktail tablet (Roche) using a 20G needle.

Equal amounts of protein were incubated with anti-V5-agarose (Abcam, ab1229) or anti-FLAG M2 affinity gel (Sigma-Aldrich, A2220) and processed by Western blotting.

Madin-Darby canine kidney (MDCK, kind gift of Prof. Kai Simons, MPI-CBG, Dresden, Germany) cells were cultured using Dulbecco's Modified Eagle Medium supplemented with 10% fetal bovine serum and 1% Penicillin-Streptomycin (Sigma). To generate MDCK cell lines for tetracycline-inducible knockdown of target genes, a lentivirus-based transduction system (pLVTH) was used as previously described [START_REF] Wiznerowicz | Conditional suppression of cellular genes: lentivirus vector-mediated drug-inducible RNA interference[END_REF]. The shRNA targeting sequences used were: Anks3-i1 (5'-GGAAGATGACCTCTGCCATTG-3'), Anks3-i2 (5'-GGAGGATCGAGTCCAGGAAAT-3'),

Ift88-i (5'-GAAGGCAGCTGAATTCTAT-3'), Kif3a-i (5'-AGGCTAGAGCTGAATTAGAG- 3'), Lkb1-i1 (5′-GCTGGTGGACGTGTTATAC-3′), Lkb1-i2 (5′- GGTGGACGTGTTATACAAT-3), Luciferase (5′-CGTACGCGGAATACTTCGA-3′), Nek7- i1 (5'-GAGTCATGCATAGAGATATAA-3'), Nek7-i2 (5'-CCAGCTAATGTGTTCATTACA- 3'), Nphp1-i (5′-GGTTCTCAGTAGACATGTA-3′) (Delous et al, 2009), Nphp4-i (5′- GCCCATCGGTGTCTACACA-3′) (Delous et al, 2009), Strada-i (5′- CAAGTACAGTGTCAAGGTTCT-3′) and Stradb-i (5′-GAACACAAGTTGAATCACTCA-3′).
The efficiency of the knock-down was verified by qRT-PCR as described below (primer list in Appendix Table S1) and/or Western blot. YFP.NPHP1, Flag.LKB1 (rescue), YFP.LKB1, STRADa.YFP and STRADb.YFP expressing MDCK lines were generated with a retroviral transduction system (pLXSN) as previously described (Boehlke et al, 2010a).

Pkd1 null MDCK cell lines were engineered with transcription activator-like effector 1% Triton X100) using a 20G needle. Lysis buffers were supplemented with 1mM

Na3VO4, 50mM NaF, 5mM -glycerophosphate and protease inhibitor cocktail tablet (Roche). Protein content was determined with Pierce BCA protein assay kit (Thermo Fisher Scientific). Equal amounts of protein were resolved on 4-15% Mini-PROTEAN TGX TM Gel (Bio-Rad) under reducing conditions, transferred, incubated with primary and secondary antibodies and visualized on film according to standard protocols. Band density was calculated and normalized using LabImage 1D L340 software.

CCL2 ELISA

For CCL2 measurement, 150,000 MDCK cells/cm² were seeded with or without Tetracyclin (5µg/mL) for 8 days on polycarbonate membranes (COSTAR, 3401). Cell culture supernatants were collected after 24 hours serum deprivation and particulates were removed by centrifugation. Canine CCL2 was measured using ELISA (Canine CCL2/MCP-1 Quantikine ELISA kit, R&D systems, CACP00). Specimens, standards, and reagents were prepared according to the manufacturer's instructions.

Immunohistochemistry

4µm sections of paraffin-embedded kidneys were submitted to antigen retrieval and avidin/biotin blocking (Vector, SP-2001). Sections were incubated with primary antibody followed by biotinylated antibody, HRP-labeled streptavidin (Southern Biotech, 7100-05, 1:500) and 3-3′-diamino-benzidine-tetrahydrochloride (DAB) revelation. Images were recorded as described above.

Immunofluorescence

4µm sections of paraffin-embedded kidneys or cells seeded on glass coverslip coated with Poly-lysine (Sigma) were submitted to antigen retrieval and avidin/biotin blocking or cell permeabilisation. The sections or coverslips were incubated with primary antibody and subsequently with the Alexa Fluor conjugated secondary antibodies or rhodamine labeled Dolichos Biflorus Agglutinin (DBA, Vector Laboratories, RL-1032, 1:100). Images were recorded using an Axiovert 200M (Zeiss) and AxioVision software (Zeiss). Confocal imaging was performed on an LSM 510 Duo microscope (ZEISS) using ZenBlack Software (Zeiss).

Flow cytometry and cell sorting

After perfusion with 10mL cold, sterile PBS, kidneys from 10 weeks old Lkb1 tub mice and littermate controls or 12 weeks old iPkd1 Tub mice, iPkd1 Tub ; iKif3a Tub mice and littermate controls were harvested, de-capsulated, minced with fine scissors, placed into a mixture of collagenase D (Worthington Biochemical) and DNase I (Roche), and shaken at 37°C for 35 min, as previously described [START_REF] Triantafyllopoulou | Proliferative lesions and metalloproteinase activity in murine lupus nephritis mediated by type I interferons and macrophages[END_REF]. The cell suspension was centrifuged at 1200 rpm for 6 minutes at 4°C. Cells were then triturated through nylon mesh to obtain single-cell suspensions and stained with primary antibody, DAPI (Molecular Probes) followed by Streptavidin V500 (BD Horizon) to label biotinylated antibodies. Flow cytometry was performed using a BD LSR Fortessa cytometer (BD Biosciences) and the results were analyzed with FlowJo software (TreeStar).

Mass spectrometry (MS)

Kidneys from 15-weeks old C57BL/6J male mice (n=6) were perfused with ice cold PBS supplemented with 1mM Na3VO4, 50mM NaF, 5mM -glycerophosphate and protease inhibitor cocktail tablet (Roche), the medulla separated from the cortex and homogenized in CHAPS lysis buffer as described above. After lysate pre-clearing with protein G-conjugated Sepharose beads (GE Healthcare), 10 mg were incubated on a rotating wheel for 2h at 4°C with 50µg antibody. Protein G-conjugated Sepharose beads were added and incubated on a rotating wheel for 1h at 4°C. The beads were collected by centrifugation and washed five times with CHAPS lysis buffer. Protein was eluted by heating in 2X Laemmli Buffer containing 100mM DTT followed by alkylation using 120mM iodoacetamide for 20 min at 20°C in the dark. Protein mixtures were separated by SDS-PAGE (4-12% Bis-Tris mini gradient gel), the lanes cut into 5 equal slices and in-gel digested with trypsin. Resulting peptide mixtures were processed on STAGE tips [START_REF] Rappsilber | Protocol for micro-purification, enrichment, prefractionation and storage of peptides for proteomics using StageTips[END_REF]. Three independent biological replicates were analyzed. Samples were measured on LTQ Orbitrap XL mass spectrometer (Thermo Fisher Scientific) coupled either to an Agilent 1200 nanoflow-HPLC (Agilent Technologies GmbH) or an Eksigent NanoLC-ultra. HPLC-column tips (fused silica) with 75µm inner diameter were self-packed with Reprosil-Pur 120 ODS-3 to a length of 20 cm. No pre-column was used.

Peptides were injected at a flow of 500nl/min in 92% buffer A (0.5% acetic acid in HPLC gradient grade water) and 2% buffer B (0.5% acetic acid in 80% acetonitrile, 20% water).

Separation was achieved by a linear gradient from 10% to 30% of buffer B at a flow rate of 250nl/min. The mass spectrometer was operated in the data-dependent mode and switched automatically between MS (max. of 1 x10 ions) and MS/MS. Each MS scan was followed by a maximum of five MS/MS scans in the linear ion trap using normalized collision energy of 35% and a target value of 5,000. Parent ions with a charge states of z = 1 and unassigned charge states were excluded from fragmentation. The mass range for MS was m/z = 370 to 2,000. The resolution was set to 60,000. MS parameters were as follows: spray voltage 2.3 kV; no sheath and auxiliary gas flow; ion transfer tube temperature 125⁰C.

MS data analysis

The MS raw data files were uploaded into the MaxQuant software version 1.4.1.2 [START_REF] Cox | MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification[END_REF], which performs peak detection, generates peak lists of mass error corrected peptides and data base searches. A full length mouse database containing common contaminants, such as keratins and enzymes used for in-gel digestion, (based on IPI human version 3.68) was employed, carbamidomethylcysteine was set as fixed modification and methionine oxidation and protein amino-terminal acetylation were set as variable modifications. Three miss cleavages were allowed, enzyme specificity was trypsin/P, and the MS/MS tolerance was set to 0.5Da. The average mass precision of identified peptides was in general less than 1ppm after recalibration. Peptide lists were further used by MaxQuant to identify and relatively quantify proteins using the following parameters: peptide, and protein false discovery rates (FDR) were set to 0.01, maximum peptide posterior error probability (PEP) was set to 0.1, minimum peptide length was set to 6, minimum number peptides for identification and quantitation of proteins was set to one which at least was unique, and identified proteins have been re-quantified.

Antibodies

Antibodies were used against:

For western blotting: AMPK(Cell signaling Technology, 2532, 1:1,000), ANKS3

(Eurogentec, rabbit polyconal, directed against mouse ANKS3 556-656, 1:1,000), α-TUBULIN (Sigma, T5168, 1:20,000), β-ACTIN (Sigma, A1978, 1:60,000), FLAG (M2 clone, Sigma, F-3165, 1:6,000), IFT88 (ProteinTech, 13967-1-AP, 1:1,000), KIF3a (BD For immunoprecipitation assay: Goat anti-LKB1 (M-18, Santa Cruz Biotechnology, sc-5640) and goat IgG (Santa Cruz Biotechnology, sc-2028).

Mouse Microarray gene expression

Total RNAs were extracted and purified from 5-week old control and Lkb1 Tub kidneys (5 mice per genotype), using RNeasy Mini Kit (Qiagen) according to the manufacturer's protocol. RNA quality was checked using a Fragment Analyzer™ (Advanced Analytical Technologies). cDNAs were generated and hybridized on Affymetrix GeneChip® Mouse Transcriptome Arrays 1.0 according to the GeneChip®WT Plus assay protocol. Arrays were normalized using the Robust Multichip Algorithm (RMA) and mapped to transcript clusters using the R Bioconductor packages oligo (Version 1.36.1) (Carvalho & Irizarry, 2010) and mta10sttranscriptcluster.db (Version 8.4). Downstream analysis considered only Entrez annotated transcripts. If multiple transcripts mapped to the same Entrez ID, the one with the largest interquartile Range between samples was chosen. The data has been deposited at GEO and is available to the reviewers under the link listed at the end of this section.

RNAseq gene expression in MDCK cells

Total RNA was obtained and verified as described above from MDCK cells with and without tetracycline induced knock-down of LKB1 (2 independent experiments per condition). Sequencing of fragmented cDNA was carried out on a HiSeq 2500 instrument (Illumina) at GATC Biotech laboratory (Konstanz, Germany). The 50 bp paired-end reads were pseudo-aligned to the dog transcriptome (CanFam3.1) and quantified using kallisto [START_REF] Braun | Ciliopathies. Cold Spring Harbor perspectives in biology[END_REF]. Downstream analysis considered only Entrez annotated transcripts.

The data has been deposited at GEO and is available to the reviewers under the link listed at the end of this section.

Microarray and RNAseq data analysis

Principal component analysis was done using the R labdsv package (Version 1.8).

Counts from the RNAseq data were log2 transformed prior to analysis and only the 1000 most varying transcripts were considered. Differential gene expression was calculated using limma [START_REF] Ritchie | limma powers differential expression analyses for RNA-sequencing and microarray studies[END_REF] and sleuth (Pimentel H., 2016) for the mouse microarray and dog RNAseq data, respectively using q-value < 0.05 as significance cutoff. Functional enrichment of differentially regulated genes was calculated from a conditional hypergeometric test as implemented in the R Bioconductor GOstats package [START_REF] Falcon | Using GOstats to test gene lists for GO term association[END_REF]) (p-value < 0.05) and semantic similarity among GO terms was measured via the GOSemSim package [START_REF] Yu | GOSemSim: an R package for measuring semantic similarity among GO terms and gene products[END_REF].

Statistical Analysis

Data were expressed as means or as means ± SD. Differences between the experimental groups were evaluated using one-way ANOVA, followed when significant (P < 0.05) by the Tukey-Kramer test. When only two groups were compared, two-tailed paired t test or Mann-Whitney test was used as appropriate. For Kaplan Meier survival curves, Log-rang test was applied. The statistical analysis was performed using GraphPad Prism V6 software. For cell culture, the normal distribution of experiment replicates was systematically assumed. For animal studies, the aspect of the distribution was used to assume or not the normal distribution. Differences in variance were determined when ANOVA followed by Tukey-Kramer test, ns not statistically different.

  ; Fig 1A, B and Fig EV1A-C) but the number and morphology of cilia was unchanged (Fig EV1D -F). The first sign of a renal disturbance was impaired urine concentration, which occurred at 5 weeks (Fig 1C and Fig EV1G -I); MRI (magnetic resonance imaging) studies confirmed that increased amounts of urine were present in the renal pelvis and occasionally demonstrated a few cysts (Fig 1C). Macroscopically, the kidneys diminished in size over time (Fig EV1J, K, Appendix Fig S1). The occurrence of cysts was noted at the cortico-medullary junction (Fig 1C, F: 14 and 23 weeks). Histology revealed dilated tubules, thickened tubular basement membranes, interstitial inflammation as well as fibrosis (Fig 1G, H). Collagen synthesis, a marker for extracellular matrix deposition, was increased (Fig EV1L) and renal failure ensued (Fig 1D, E). Analogous to humans with Peutz-Jeghers syndrome, heterozygote animals had normal renal function and histology (Appendix Fig S1). These findings show that LKB1 is required for normal morphology and function of the kidney.

  STRADa localized to cilia in MDCK cells (Fig 5C). Furthermore, inducible knock-down of STRADb decreased the amount of LKB1 in the cilium (Fig 5D, E and Appendix Fig S3).

  cells (Fig 6B, C), analogous to our findings in LKB1 depleted cells. Neither LKB1 or other members of the regulatory complex were consistently altered in their expression (Appendix Fig S4). When we ablated cilia through depletion of KIF3a or IFT88 in Pkd1 null cells, we found a marked decrease in Ccl2 (Fig 6D and Appendix Fig S3). Simultaneous LKB1 depletion in PKD1 knock-out cells, however, did not change Ccl2 expression compared to PKD1 deletion alone (Fig EV3H and Appendix Fig S3) indicating

  , these animals had a strongly ameliorated phenotype (Fig 6E, F). In line with our in vitro findings, disruption of ciliogenesis prevented Ccl2 up-regulation in Pkd1 deficient kidneys (Fig 6G). Concurrently, cilia ablation also decreased the numbers of CCR2 + mononuclear phagocytes (Fig 6H -K).This finding supports the hypothesis that cilia induce CCL2 in Pkd1 deficient kidneys to recruit macrophages and drive cyst growth. However, it leaves the possibility that an unknown cilia signal other than CCL2 drives cyst growth, affecting inflammation and immune cell mediated CCL2 expression by indirect means. To investigate this possibility we inactivated Pkd1 and Ccl2 simultaneously in renal epithelial cells using the same Credriver. As expected, this resulted in fewer macrophages and a strongly ameliorated phenotype. This finding confirms that tubular CCL2 drives ADPKD severity in-vivo. Our findings from in vitro systems and an ADPKD disease model demonstrate that PKD1 interacts with the LKB1 regulatory module to inhibit a ciliary signal inducing CCL2 (Fig 8C). A Pkd1 mutation releases the inhibitory signal, promoting increased levels of CCL2, the accumulation of CCR2 + mononuclear phagocytes and cyst growth, while the ablation of cilia or inactivation of CCL2 in PKD1 mutant epithelial cells in the kidney prevents this cascade (Fig 8D -F).

Flag.

  LKB1 for rescue experiment was cloned from human cDNA into pLXSN in-frame with Flag tag. YFP.LKB1, STRADa.YFP and STRADb.YFP were cloned from human cDNA into pLXSN in-frame with N-terminal (LKB1) or C-terminal (STRAD constructs) YFP variant. The primers used for cloning are listed in Appendix Table

For

  immunostaining on kidney sections or MDCK cells: acetyl-alpha-Tubulin (Lys40) (D20G3, Cell signaling Technology, 5335, 1:100), acetylated Tubulin (Sigma, T6793, 1:250), ANKS3: for kidney sections (Eurogentec, rabbit polyconal, directed against mouse ANKS3 290-395, 4µg/mL); for MDCK cells (Novus Biologicals, NB100-61625, 1:100), AQP1 (Santa Cruz Biotechnology, sc-20810, 1:500), AQP2 (Santa Cruz Biotechnology, sc-9882, 1:500), F4/80 (Clone Cl:A3-1, BioRad, MCA497R, 1:100), GFP (Abcam, ab13970, 1:400), IgG (Santa Cruz Biotechnology, sc-2027, 4µg/mL), LKB1 (D60C5F10, Cell signaling Technology, 13031, 1:1,000 for kidney section, 1:100 for MDCK cells), pAMPK T172 (Cell signaling Technology, 2535, 1:100), pS6RP S235/236 (Cell signaling Technology, 4858, 1:100) and THP (Serotec, 8595-0054, 1:500).For Flow cytometry: The following antibodies were used: CD45 (30-F11), B220 (RA3-6B2), CD3 (145-2C11), CD19 (MB19-1), CD5 (53-7.3), CD11b (M1/70) (all from eBioscience), NK1.1 (PK136, BD Pharmingen), Ly6G (1A8, BD Bioscience), F4/80 (Bio-RAD) and CCR2 (48607, R&D Systems).

  Figure legends:

  Figure 3.

Figure 4 .

 4 Figure 4. Monocytes and CCR2 + macrophage accumulation in the kidneys of Lkb1 Tub mice

Figure 5

 5 Figure 5.

Figure

  Figure EV3.

Figure EV4 .

 EV4 Figure EV4.

Acknowledgements

We thank Barbara Joch and Temel Kilic for technical assistance and Prof David Bennett for critical appraisal of the manuscript. We thank the histology facility (S.F.R Necker INSERM US24, Paris, France) for technical assistance and the ARC foundation for funding the whole slide scanner. Grant Support: Amandine Viau: ERA-EDTA ALTF 84-2011 and FRM ARF20150934110; Frank Bienaimé: EMBO ALTF 927-2013; E. Wolfgang Kuehn: Else Kröner-Fresenius-Stiftung 2011_A87 and Deutsche Forschungsgemeinschaft KFO 201, KU 1504/5-1 and SFB1140; Melanie Boerries and Hauke Busch: Deutsche Forschungsgemeinschaft SFB850; Antigoni Triantafyllopoulou: Deutsche Forschungsgemeinschaft SFB1160; Tobias B. Huber: Deutsche Forschungsgemeinschaft CRC1140, CRC 992, HU 1016/8-1 and Heisenberg program, BMBF (01GM1518C), European Research Council-ERC grant 616891, H2020-IMI2 consortium BEAt-DKD; Michael Köttgen: SFB 1140 and SFB 152: Melanie Boerries: German Federal Ministry of Education and Research (BMBF) FKZ 01ZX1409B. The authors declare that they have no conflict of interest

Data Availability

Microarray data and RNAseq data have been deposited at GEO and are available under the following links: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=ehyzwqwsvdcdpap&acc=GSE860 09. http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=ozujmguqjvsdnux&acc=GSE8601 0 Data information: In (A, B, F -H), mean ± SD. Paired t test, *P<0.05, **P<0.01, ***P<0.001, ns not statistically different. In (E) each circle represents one biological replicate. Bars indicate mean. Paired t test, *P<0.05.

nucleases (TALENs) as described [START_REF] Hofherr | Efficient genome editing of differentiated renal epithelial cells[END_REF]. Loss of Pkd1 was validated by genomic PCR and RT-PCR (primer list in Appendix Table S1). For CCL2 expression analysis, 150,000 cells/cm² were seeded with or without Tetracyclin (5µg/mL) for 6 days on polycarbonate membranes (COSTAR,3401). Total RNAs were extracted after 5 hours serum deprivation with or without AICAR treatment (1mM, LC Laboratories) and qRT-PCR was performed (primer list in Appendix Table S1). For immunofluorescence experiments, 150,000 cells/cm² cells were seeded for 10 days on glass coverslip coated with Poly-lysine with or without Tetracyclin stimulation. All cells were regularly tested for mycoplasma contamination and were mycoplasma free.

Quantitative real-time PCR (qRT-PCR)

Total RNAs were obtained from whole kidneys or cells using RNeasy Mini Kit (Qiagen) and reverse transcribed using SuperScript III First-Strand Synthesis SuperMix for qRT-PCR (Invitrogen) according to the manufacturer's protocol. qRT-PCR was performed on a LightCycler 480 (LC 480, Roche). Gapdh, Sdha, Hprt and/or Rpl13 were used as the normalization controls [START_REF] Vandesompele | Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes[END_REF]. Each biological replicate was measured in technical duplicates. The primers used for qRT-PCR are listed in Appendix Table S1.

Western blot

Fresh kidney medulla was homogenized in lysis buffer (50mM G, H. Ccl2 mRNA expression in MDCK cells expressing inducible shRNA against the indicated targets (+ Tet). Kif3a-i (n=7), Ift88-i (n=4), Kif3a-i; Lkb1-i1 (n=3) and Ift88-i; Lkb1-i1 (n=4). See also Appendix Figure S3J -M. J, K. Flow cytometry analysis (J) and absolute numbers (K) of CCR2 + monocytes (F4/80 lo CD11b hi CCR2 + , black square) in control, iPkd1 Tub and iPkd1 Tub ; iKif3a Tub mice at 12 weeks.

Conflict of interest