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Altered regulation of the PINK1 locus: a link between type 2 diabetes and neurodegeneration?

Altered regulation of the PINK1 locus: a link between type 2 diabetes and neurodegeneration?
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  The FASEB Journal   •  Research Communication  Altered regulation of the PINK1 locus: a link betweentype 2 diabetes and neurodegeneration? Camilla Scheele,* ,1  Anders Rinnov Nielsen, †,§ Tomas B. Walden, ‡,§ Dean A. Sewell, § Christian P. Fischer, † Robert J. Brogan,* Natasa Petrovic,* ,‡ Ola Larsson,*Per A. Tesch,  Kristian Wennmalm,* Dana S. Hutchinson, ‡,¶ Barbara Cannon, ‡,§ Claes Wahlestedt,* ,#  Bente K. Pedersen, † and James A. Timmons* ,‡,§,1 *Center for Genomics and Bioinformatics, Karolinska Institutet, Stockholm, Sweden;  † Centre of Inflammation and Metabolism, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; ‡ The Wenner-Gren Institute, The Arrhenius Laboratories, Stockholm University, Stockholm, Sweden; § School of Life Sciences, Heriot-Watt University, Edinburgh, Scotland, UK;   Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden;  ¶ Department of Pharmacology, Monash University, Clayton, Victoria, Australia; and  # Department of Biochemistry,The Scripps Research Institute, Jupiter, Florida, USA   ABSTRACT  Mutations in PINK1 cause the mitochon-drial-relatedneurodegenerativediseaseParkinson’s.Here we investigate whether obesity, type 2 diabetes, or inactiv-ity alters transcription from the  PINK1  locus. We utilizeda cDNA-array and quantitative real-time PCR for geneexpression analysis of muscle from healthy volunteersfollowing physical inactivity, and muscle and adiposetissue from nonobese or obese subjects with normalglucose tolerance or type 2 diabetes. Functional studies of PINK1 were performed utilizing RNA interference in cellculture models. Following inactivity, the  PINK1  locus hadan opposing regulation pattern (PINK1 was down-regu-lated while natural antisense PINK1 was up-regulated). Intype 2 diabetes skeletal muscle, all transcripts from the PINK1  locus were suppressed and gene expression corre-lated with diabetes status. RNA interference of PINK1 inhuman neuronal cell lines impaired basal glucose uptake.In adipose tissue, mitochondrial gene expression corre-lated with PINK1 expression although remained unal-tered following siRNA knockdown of Pink1 in primary cultures of brown preadipocytes. In conclusion, regula-tion of the  PINK1  locus, previously linked to neurodegen-erative disease, is altered in obesity, type 2 diabetes andinactivity, while the combination of RNAi experimentsand clinical data suggests a role for PINK1 in cell ener-getics rather than in mitochondrial biogenesis.—Scheele,C., Nielsen, A. R., Walden, T. B., Sewell, D. A., Fischer, C.P., Brogan, R. J., Petrovic, N., Larsson, O., Tesch, P. A., Wennmalm, K., Hutchinson, D. S., Cannon, B., Wahlest-edt, C., Pedersen, B. K., Timmons, J. A. Altered regula-tion of the PINK1 locus: a link between Type 2 diabetesand neurodegeneration?  FASEB J.  21, 3653–3665 (2007) Key Words: metabolism     inactivity     mitochondria     altered gene regulation  The interaction between physical inactivity , ge-netically determined aerobic capacity and the subse-quent role of mitochondrial “dysfunction” in precipi-tating metabolic disease is extremely complex andtypically confounds the interpretation of disease phe-notypes. Some have found a relationship between mi-tochondrial capacity and insulin resistance (1), andgreat importance has been attached to recent observa-tions that PGC-1  , a transcriptional cofactor and amaster regulator of mitochondrial biogenesis, is down-regulated in the skeletal muscle of type 2 diabetespatients (2). PGC-1   is involved in several metabolicpathways (3, 4) making it a plausible “disease gene”.However, skeletal muscle gene expression changes incomplex diseases, such as type 2 diabetes, are difficult to interpret. For example, we have demonstrated that short term physical inactivity alone can induce similarchanges in human skeletal muscle PGC-1   expressionto those found in type 2 diabetes (5), such that theinteraction between diabetes  per se   and inactivity meritsfurther investigation. It is also plausible that othermitochondrially associated genes participate in provid-ing a link between mitochondrial function, physicalinactivity, obesity, and type 2 diabetes.To identify novel candidate genes associated withone physical inactivity model (5) we utilized a smallcustom cDNA array platform that was enriched withdruggable (6) protein targets. We identified a modest number of candidate genes, partly reflecting the lim-ited performance of this particular custom array. Oneof the genes we identified was PTEN induced putativekinase 1 (PINK1). PINK1 is a putative serine-threoninekinase that has been linked to a recessive form of familial parkinsonism (7–10). Although little is knownabout the etiology of diabetes in Parkinson’s disease, up 1 Correspondence: C.S., Center for Genomics and Bioinfor-matics, Karolinska Institutet, 171 77 Stockholm, Sweden.E-mail:; J.A.T., School of LifeSciences, Heriot-Watt University, Edinburgh EH14 4AS, Scot-land, U.K.. E-mail: 10.1096/fj.07-8520com 36530892-6638/07/0021-3653 © FASEB  to 80% of the patients are claimed to have impairedglucose tolerance (11), while several pieces of evidencepoint to a link between Parkinson’s disease and mito-chondrial dysfunction (12), an association common with diabetes. Over-expressed and endogenous PINK1localizes to the mitochondria (8, 10, 13) and very recently it has been demonstrated that PINK1 plays acritical role in  Drosophila   oxidative flight muscle (14–16) where mutated PINK1 resulted in loss of mitochon-drial architecture and muscle function and was associ-ated with increased ROS production. Indeed,antioxidant therapy could rescue neuronal cell deathinduced by knockdown of PINK1 in  Drosophila   (17),thus providing a link between the function of PINK1and a postulated role of ROS in the etiology of insulinresistance (18).In addition to PINK1, there are a number of tran-scripts produced from the human  PINK1  locus (Fig. 3),including Dolichyl-diphosphooligosaccharide-proteinglycosyltransferase (DDOST) and a natural antisensePINK1 molecule (19). Interestingly, DDOST translatesinto the AGE-R1 scavenger receptor, a counter regula-tory mechanism for advanced glycation end product (AGE)-induced oxidative stress (20–22). AGE forma-tion is enhanced by hyperglycemia (23), has beenlinked to diabetic complications (24–26) and shown toaccumulate in neurodegenerative disease (27). Partly overlapping with the 3  -end of DDOST and partly complementary to PINK1 is naPINK1, a cis-encodednatural antisense to PINK1 that we have recently func-tionally verified (19). Given the number of potentialinteractions between these genes and impaired metab-olism, we selected the  PINK1  locus for investigation insubjects with type 2 diabetes (with and without obesity). We did this simultaneously in two insulin sensitiveorgans (muscle and adipose tissue) and related geneexpression to measures of metabolic and physical fit-ness. In addition, we profiled PGC-1   and two mito-chondrial genes (mtND4 and Citrate synthase) to allow for direct comparison with previously published data(2, 28, 29), and evaluated the function of PINK1 usingRNA interference (RNAi) in cell based models. Geneexpression changes are presented from human modelsof physical activity (30) and inactivity (5, 19) to provideadditional context to the cause-effect interpretation of the clinical data. MATERIALS AND METHODS Human inactivity model and custom gene array analysis  We utilized a model of skeletal muscle disuse (31–33), toimpose five weeks of muscle inactivity in one leg of healthy  volunteers. Six healthy adult subjects, four men and two women, volunteered for this study. At the time of beingrecruited, the subjects did not participate in any regulartraining programs. A written consent was given after theprocedures and risks associated with participation in the study had been explained. The experimental protocol was ap-proved by the Institutional Review Board at the University andthe study was conducted in accordance with the Declarationof Helsinki as revised in 2000. The subjects were 30–56 y, witha body fat range of 9–25% (calculated from biceps, triceps,suprailiac, and front thigh skinfolds, using a Harpendencaliper). The subjects had a body mass range of 57–91 kg anda height range of 165–185 cm. The physiological results andglobal changes in muscle volume from this study have beenreported elsewhere (5, 34). Muscle biopsies were obtainedfrom the  m Soleus   before and after this intervention period,and RNA isolation, real-time quantitative PCR and calcula-tions were carried out as described previously (5).For the custom microarray analysis, total RNA was pre-pared as described below. Data appear in supplementary File 1. All samples were labeled and hybridized as exten-sively described previously (35). The software used for theimage analysis of the arrays was SpotReader ( Data analysis was performed using theR environment and Bioconductor (36) unless otherwisestated. The images were digitalized using Quantarray andnormalized using nonprint-tip loess normalization (37) with-out background subtraction as this gives higher accuracy (38). Significantly differentially expressed genes were identi-fied using the Significance Analysis of Microarrays (SAM)algorithm using the paired test setting as previously discussed(39). The significant gene list is supplied as an Excel spread-sheet. However, due to the limitation of the arrays, this dataset should only be considered pilot data. Obesity and type 2 diabetes cohort  Using a cross-sectional case-control design, participants forthis study were divided into 4 groups according to thepresence or absence of a diagnosis for type 2 diabetes andaccording to body mass index (BMI)  27 or  35. All subjects( n   53) were recruited by advertising in a local newspaperand information of diagnosis of type 2 diabetes was based oninformation from each subject respectively. To verify correct diagnosis, the World Health Organization (WHO) diagnosticcriteria for diabetes were employed. Exclusion criteria weretreatment with insulin, recent or ongoing infection, history of malignant disease or treatment with antiinflammatory drugs.Characteristics are given in  Table 1  for the four main groups: 1)   normal glucose tolerant, nonobese ( n   12);  2)   normalglucose tolerant, obese ( n   14);  3)   type 2 diabetes, nonobese,( n   13);  4)   type 2 diabetes, obese ( n   14). Participants weregiven both oral and written information about the experi-mental procedures before giving their written informed con-sent. The study was approved by the Ethical Committee of Copenhagen and Frederiksberg Communities, Denmark ( 01–141/04), and performed according to the Declara-tion of Helsinki. The Universities of Copenhagen, KarolinskaInstitutet and Heriot-Watt provided additional ethics ap-proval for all molecular analysis. Clinical evaluation protocol Participants reported between 8:00 and 10:00 a.m. into thelaboratory after an overnight fast. Subjects did not take theirusual medication for 24 h preceding the examination, andsubjects with type 2 diabetes did not take hypoglycemicmedicine for one week preceding the examination day. Theabdominal and limb circumferences were measured, as werebody mass and height for BMI calculations. Sphygomanomet-ric measurement of the brachial arterial blood pressure wasperformed on the participants resting in supine position.Blood samples were drawn from an antecubital vein. On thesame day, biopsies were obtained from muscle and adiposetissue; the subjects performed an oral glucose tolerance test  3654 Vol. 21 November 2007 SCHEELE  ET AL. The FASEB Journal  (OGTT), an aerobic capacity (fitness) test and were scannedusing a dual-energy X-ray absorptiometry (DEXA) wholebody scanner for determining body composition. Muscle and adipose tissue biopsies Muscle biopsies from the patient cohort were obtained fromthe  m vastus lateralis   of   m quadriceps femoris   using the percuta-neous needle method with suction (40). Prior to each biopsy,local anesthesia (lidocaine, 20 mg ml –1 ; SAD, Denmark) wasapplied to the skin and superficial fascia of the biopsy site. Adipose tissue biopsies were sampled from the abdominalsubcutaneous adipose tissue by the percutaneous needlebiopsy technique with suction, preceded by a subcutaneousinjection of lidocaine. Visible blood contamination was care-fully removed and all biopsies were frozen in liquid nitrogenand subsequently stored at –80°C until further analysis.  Aerobic capacity (fitness) test and body composition Peak aerobic capacity was determined by the Åstrand-Ryhmingindirect test of maximal oxygen uptake (VO 2max ) (41). Totalbody and regional fat (kg) were assessed by dual-energy X-ray absorptiometry (DEXA) GE Medical Systems lunar, Prodigy  Advance). The scanner was calibrated daily and a spinephantom was scanned weekly. Software version 8.8 was usedto estimate regional and total fat and lean soft tissue. Nosandbags or pillows were used. Landmarks were set to sepa-rate appendages (upper and lower limbs) from truncal re-gions: (1) the upper limb-region was separated from trunk by a line extended from the head of humerus and the glenoidfossa of the scapula; (2) The legs consisted of the tissueextended from the inferior border of the ischial tuborosity tothe distal tip of the toes. Lean soft tissue is directly correlatedto skeletal muscle mass and appendicular skeletal musclemass (ASM) is calculated as total muscle mass in upper- andlower-limbs, which is directly correlated to total body skeletalmuscle mass (42). Relative truncal fat is calculated as truncalfat divided by total body fat (43, 44) and used as an estimateof fat distribution, assumed to correlate to the amount of  visceral adipose tissue (45). Self reported physical activity wasdetermined as previously discussed (46). Blood analyses Plasma was obtained by drawing blood samples into glasstubes containing EDTA, and serum was obtained by drawingblood into glass tubes containing a clot-inducing plug. Thetubes were immediately spun at 3500 g for 15 min at 4°C andthe supernatant was isolated and stored at –20°C until analy-ses were performed. Plasma insulin were analyzed by radio-immunoassay (Insulin RIA 100, Amersham Pharmacia Bio-tech, Uppsala, Sweden) and plasma glucose was determinedusing an automatic analyzer (Cobas Fara, Roche, France)both as described previously (47). All samples and standards were run as duplicates, and the mean of duplicates was usedin the statistical analyses. Oral glucose tolerance test (OGTT) Blood samples were drawn before, and 1 and 2 h after,drinking 500 ml of water containing 75 g of dissolved glucose.The WHO diagnostic criteria were applied (48). Normalglucose tolerance (NGT) was defined as fasting venousplasma glucose    6 mM and   7.8 mM 2 h after the oralglucose load, and type 2 diabetes as fasting venous plasmaglucose  7.0 mM or venous plasma glucose  11.1 mM 2 hafter the oral glucose load. HOMA2-IR was determinedaccording to current guidelines (49, 50). Cell culture and transfection  All cell culture reagents were purchased from GIBCO (In- vitrogen, Carlsbad, CA, USA) unless otherwise stated. Theneuroblastoma cell line SK-N-MC was subcultured in minimalessential media (MEM)    Earle’s supplemented with 10%fetal bovine serum (FBS), 2 mM L-glutamine, 1 mM sodiumpyruvate, nonessential amino acids, 100 U/ml penicillin, and100   g/ml streptomycin. The neuroblastoma cell line SH-SY5Y was subcultured in DMEM/F12 supplemented with 10%FBS, nonessential amino acids, 100 U/ml penicillin and 100  g/ml streptomycin. Cell cultures were maintained at 37°C in5% CO 2 . Transfection was performed using 0.25% Lipo-fectamine 2000 (Invitrogen) and 20 nM siRNA, according tothe manufacturer’s protocol. Following 48 h, cells wereTABLE 1.  Demographic characteristics  NGT non-obese NGT obese DM2 non-obese DM2 obese n   12 14 13 14Gender 7 F, 5  m  4 F, 10  m  6 F, 7  m  6 F, 8  m  Age 53.5  4.1 47  2.1 53.9  2.3 53.1  2.5Current smoker (%) 41.7 14.3 30.8 21.4BMI, kg/m2 24.4  0.9 36.0  0.7***††† 25.8  0.5 37.0  1.6***†††Previously diagnosed diabetes (%) 0 0 100 71Physical activity score 3.4  0.4 2.8  0.6 2.6  0.6 1.6  0.4 VO 2 max/kg 40.4  6.2 26.2  3.5*** 28.9  4.0** 22.5  4.9*** VO 2 max/ffm 58.5  3.1 44.6  1.8* 42.8  1.8* 40.5  2.2**Fasting glucose (m m)  5.1  0.2 5.3  0.1 9.9  1.5***‡‡‡ 8.6  0.5*‡Two hour glucose (m m)  5.5  0.5 6.0  0.3 17.7  2.1***‡‡‡ 15.3  0.7***‡‡‡Fasting insulin (pmol/l) 33  5 72  12 51  8 161  25***†††‡‡‡Two hour insulin (pmol/l) 285  115 321  46 333  78 621  121HOMA2 IR 0.63  0.1 1.34  0.2 1.25  0.2 3.24  0.5***†††‡‡‡Hemoglobin A1c (%) 5.5  0.5 5.6  0.1 7.7  0.7**‡‡ 6.9  0.3 Adiponectin (ng/ml) 7383  1437 6380  784 5221  889 4200  475 P   values were relative to NGT non-obese (*; **; ***); DM non-obese (†; ††; †††) or NGT obese (‡; ‡‡; ‡‡‡) ( P   0.05;  P   0.01;  P   0.001). Values are mean ( se ) and one-way ANOVA and Tukey’s post-tests (providing the  P   values) were used. 3655THE  PINK1  LOCUS IN OBESITY AND TYPE 2 DIABETES  harvested for RNA isolation or, following 72 h, used forglucose uptake. PINK1 was knocked down with either PINK1-siRNA-1 ( n   9) or PINK1-siRNA-2 or-3 ( n   9). The siRNAstargeting PINK1 (Table S1) were prevalidated or predesignedsiRNAs from Ambion (Austin, TX, USA; PINK1-siRNA-1: ID#1199; PINK1-siRNA-2: ID #1294 and PINK1-siRNA-3:ID#103456) and thus designed and chemically synthesized by  Ambion. The control siRNA was predesigned by Ambion tonot target any gene in the genome (Silencer ® Negative Con-trol#1, Ambion).Primary brown preadipocyte cell culture and differentia-tion: Male NMRI mice (age 3–4 wk; B&K, Stockholm, Swe-den) were sacrificed by CO 2 , and brown adipose tissue (BAT)(from the interscapular, cervical and axillary depots) wasisolated as described previously (51). Briefly, minced tissues were digested in a collagenase (type II, Sigma Aldrich,Stockholm, Sweden) containing buffer, for 30 min at 37°C.The cell suspension was filtered and kept on ice for 20 min. After discarding the top layer (mature adipocytes) the sus-pension was filtered and washed in Dulbecco’s modifiedEagle’s media (DMEM) and resuspended in 0.5 ml culturemedia per animal. Cells were cultured in 6-well plates (Falcon,BD Biosciences, Erembodegem, Belgium) in DMEM supple-mented with 10% (v/v) newborn calf serum (HyClone, Erem-bodegem, Belgium), 2.4 nM insulin, 25   g/ml sodium ascor-bate,10mMHEPES,4mMglutamine,100U/mlpenicillin,and100  g/ml streptomycin. Culture media (1.8 ml) was added toeach well before 0.2 ml of cell suspension was added.Following 24 h in culture, cells were transfected using 0.1%Lipofectamine 2000 (Invitrogen) and 20 nM short interferingRNA (siRNA) in 2.5 ml newborn calf serum-containing cellculture media (without penicillin/streptomycin) accordingto the manufacturer’s protocol and as described above.Following 48 h of transfection, media was changed and after72 h cells were harvested for RNA isolation using TRIzol(Invitrogen). The siRNA (PINK1-siRNA-1, Table S1) target-ing PINK1 was a prevalidated siRNA from Ambion (ID #1199)and thus designed and chemically synthesized by Ambion.The control siRNA was predesigned by Ambion to not target any gene in the genome (Silencer ® Negative Control#1, Am-bion).  Western blot analysis Cells were washed twice in ice-cold PBS and harvested in alysis buffer containing 62.5 mM Tris-HCl (pH 6.8), 2% (w/v)SDS and 10% (v/v) glycerol. Protein concentration wasdetermined using the Lowry method, and 20   g proteins were separated on 12% polyacrylamide gels and transferredon to a PVDF membrane (Amersham Biosciences, Piscataway,NJ, USA) in 48 mM Tris/HCl, 39 mM glycine, 0.037% (w/v)SDS and 15% (v/v) methanol, using a semidry electro-phoretic transfer cell (Bio-Rad, Sundbyberg, Sweden). Themembrane was blocked in 5% milk for 1 h at room temper-ature and probed with indicated antibodies overnight at 4°C.The immunoblots were visualized with horseradish peroxi-dase-conjugated secondary antibodies and enhanced chemi-luminescence on Hyperfilm-ECL (Amersham Biosciences).Following immunoblotting, the membrane was stained with Amido Black and a highly abundant band of    45 kDa wasused for normalization. The band intensities were quantifiedusing ImageQuant software. Antibodies used were: COXI: Anti-OxPhos Complex IV subunit I, mouse IgG2a, monoclo-nal 1D6 (anticytochrome oxidase subunit I) (MolecularProbes, Eugene, OR, USA, Catalog#A-6403), dilution 1:1000;Parkin: Anti Parkin rabbit polyclonal antibody (Cell Signal-ing, Cat#4211), dilution 1:1000; TFAM: Rabbit polyclonal(52), kindly provided by Dr. Claes Gustafsson, KarolinskaInstitutet, Stockholm, Sweden (Dilution 1:1000). Glucose uptake assay  Following 72 h of PINK1 siRNA transfection of neuroblas-toma cells, glucose uptake was measured. Cells were serum-starved for 2 h and then washed twice with PBS.  3 H-2-deoxyglucose was added to glucose-free DMEM and appliedto the cells. Following 15 min of incubation, cells were washedtwice with cold PBS, subsequently lysed with 500   l 0.2 MNaOH, and incubated for 30 min at 60°C. 400   l were usedfor the scintillation vials and the rest (  100  l) was used fordetermine protein concentration using the Lowry method. Ineach experiment, each treatment was determined in triplicateand normalized to the protein concentration. RNA isolation and quantitative real- time PCR (qRT-PCR) Human tissue biopsies were homogenized in TRIzol (Invitro-gen) using a motor-driven homogenizer (Polytron, Kine-matica, Newark, NY, USA) and total RNA was isolated accord-ing to the manufacturer’s protocol. Total RNA was dissolvedin RNase-free water and quantified using a Spectrophotome-ter (Pharmacia Biotech, Piscataway, NJ, USA). For the cellsamples, total RNA was isolated using TRIzol (Invitrogen),according to the manufacturer’s protocol. Total RNA wasreverse-transcribed using reverse transcription reagents (Ap-plied Biosystems, Foster City, CA, USA) according to themanufacturer’s protocol. Random hexamers were used forfirst-strand cDNA synthesis. Detection of mRNA was per-formed using an ABI-PRISM ® 7000 Sequence Detection sys-tem (Applied Biosystems). Primers and MGB probes (Table1) were designed using Primer Express software (AppliedBiosystems) or obtained using the Universal Probe Library (Roche Applied Science). A preoptimized primer and probeassay for 18S rRNA was used as an endogenous control(Applied Biosystems). Primers and probes were premixed with TaqMan Universal Master Mix or SYBR  ® GREEN PCR Master Mix (Applied Biosystems) and distributed into 96-wellMicroAmp Optical barcode plates (Applied Biosystems).cDNA aliquots of 4  l were added in triplicates. The amplifi-cation of genomic DNA typically amounted to a maximumof    1% of the target gene when using the TRIzol protocol.Two-fold dilutions series were performed for all target genesand endogenous controls to determine the amplificationefficiency. Calculations and statistical analysis  All data are presented as mean  se , unless otherwise stated.The  Ct method (Applied Biosystems, User bulletin 2) wasused to calculate relative changes in mRNA abundance. Thethreshold cycle (CT) value for 18S was subtracted from theCT value for the target gene to adjust for any variations in thecDNA synthesis. For the metabolic cohort, a mean wascalculated from 18S adjusted CT-values of any target gene foreach of the four groups and the individual values in eachgroup were related to that mean. For the paired musclesamples, the preinactivity values reflect baseline gene expres-sion levels and were subtracted from the postinactivity sam-ple. For the siRNA experiments, 18S adjusted CT-values wererelated to the adjusted CT-value of the untreated sample ineach experiment, and then a mean from all experiments wascalculated. The results are presented as percentage mRNA abundance of untreated samples (mean  se ). ANOVA wasutilized to analyze both the human gene expression responsesand the cell based responses. When a significant F ratio wasachieved, post hoc analysis (Tukey) was utilized to makeindividual comparisons and generate  P  -values that are stated 3656 Vol. 21 November 2007 SCHEELE  ET AL. The FASEB Journal  in the figure legends. Sample size and significance level isshown in the figure legends for each graph. RESULTSExpression of PGC-1   and marker mitochondrialgenes in human muscle and adipose tissue Given the prevailing view that diabetes associates withmitochondrial dysfunction, we profiled some estab-lished markers of mitochondria to characterize ourcase-control cohort. As can be observed in  Fig. 1  A   and C  , both the mitochondrial complex I gene, mtND4, andCitrate synthase (CS) were significantly down-regulatedin the adipose tissue of obese, normal glucose tolerant subjects (NGT BMI  35) and nonobese type 2 diabetespatients (DM BMI  27) when compared with nono-bese, normal glucose tolerant age- and gender-matchedcontrols (NGT BMI  27). Intriguingly, in the obesediabetes group (DM BMI  35), the mitochondrial geneexpression was not reduced. In fact, for Citrate synthasethere was a significant difference between the nono-bese and the obese, type 2 diabetes patients (Fig. 1 C  ).PGC-1   was down-regulated in all three disease groupsin adipose tissue ( Fig. 2  A  ), clearly contrasting with themitochondrial gene expression profile. In skeletal mus-cle, only the DM BMI    27 group demonstrated areduction in mitochondrial gene expression (Fig. 1 B  ,  D  ), consistent with the skeletal muscle PGC-1   profile(Fig. 2 B  ). Noteworthy, 29% of the DM BMI  35 group were newly diagnosed for type 2 diabetes at the time of the investigation while 100% of the DM BMI    27group had preexisting diabetes (Table 1). However, when excluding this 29% of DM BMI  35 individualsfrom our expression analysis, no impact was noted onthe average expression values for PGC-1  , Citrate syn-thase and mtND4 (data not shown). Further analysisdemonstrated that expression of PGC-1   in adiposetissue weakly related to aerobic capacity (R  2  0.15, Fig.2 C  ), while in skeletal muscle there was no correlation(Fig. 2  D  ). Neither did PGC-1  correlate to self-reportedphysical activity (data not shown). The  PINK1  locus genes were reciprocally regulated inskeletal muscle by physical inactivity yet were allsuppressed of type 2 diabetes patients Following on from our custom array analysis, whichdemonstrated a reduction in muscle PINK1 expressiondue to inactivity (Supplementary Dataset 1); we studiedthree main transcripts produced from the  PINK1  locus( Fig. 3 ). We used qRT-PCR and confirmed that PINK1 was 40% reduced following 5 wk of inactivity in ourhealthy volunteers (5) ( Fig. 4  A  ). In contrast, naturalantisense PINK1 (naPINK1), a cis-encoded naturalantisense transcribed from the  PINK1  locus (19),tended to be up-regulated in connection with inactivity (Fig. 4 A  ). This reciprocal pattern of regulation issupported by earlier analysis from an endurance train-ing study (30) where PINK1 was significantly up-regu-lated following endurance training, while naPINK1 wassignificantly down-regulated (19). In contrast, DDOSTexpression was not altered by 5 wk of muscle inactivity (or by 6 wk of endurance training) (Fig. S1). We thensought to establish whether transcript abundance de- Figure 1.  Expression of mitochondrial genes in human adipose andmuscle tissue in obesity and type 2 diabetes ( A–D  ). Total RNA was isolatedfrom adipose and muscle biopsies in age- and gender-matched subjectsdivided into four groups: normal glucose tolerant nonobese (NGTBMI  27)  n     12 for muscle,  n     9 for adipose tissue; normal glucosetolerant obese (NGT BMI  35)  n     14 for muscle,  n     11 for adiposetissue; type 2 diabetes nonobese (DM BMI  35)  n   13 for muscle,  n   10for adipose tissue and type 2 diabetes obese (DM BMI  35)  n     14 formuscle,  n     13 for adipose tissue. Gene expression in the four different groups was measured using qRT-PCR with 18S as an endogenous control.Differences in gene expression were tested using ANOVA and subsequent Tukey post-test. Data are mean  se  and are presented as a percentage of the average expression in the control group (NGT BMI  27). * P     0.05,** P     0.01, *** P     0.001.  A)   mtND4 expression in adipose tissue.  B)   mtND4 expression in muscle tissue.  C)   Citratesynthase expression in adipose tissue.  D)   Citrate synthase expression in muscle tissue. 3657THE  PINK1  LOCUS IN OBESITY AND TYPE 2 DIABETES
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