SNPMiner Trials by Shray Alag


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Report for SNP rs1761667

Developed by Shray Alag, 2020.
SNP Clinical Trial Gene

There are 3 clinical trials

Clinical Trials


1 Inhibition of Lipolysis in Oral Cavity and Fat Perception in Humans

There are many substances naturally present in the mouth that may help us taste fat in food. Two of these substances (lipases and CD36) will be examined in this study. The presence of fat in food increases food tastiness, therefore people often over-eat high-fat foods and gain weight. The purpose of this study is to determine if blocking lipases and some genetic variations in the CD36 gene will make fatty food less tasty so that people eat less. Our hypothesis is that Orlistat and a particular gene will increase one's ability to detect fat.

NCT01128400 Obesity
MeSH: Obesity
HPO: Obesity

Hypothesis: SNPs that associate with reduced CD36 expression will be associated with higher FFA and TAG detection thresholds To test this hypothesis we will measure triolein and oleic acid taste detection thresholds in subjects who carry of the common CD36 e-SNP rs1761667 (i.e. a SNP that significantly reduces CD36 level and has a minor allele frequency of 38-48%).

Primary Outcomes

Description: We will measure oleic acid detection levels as a marker of subjects' ability to detect free fatty acids. Oleic acid taste detection thresholds were separately assessed using a three-alternative forced-choice (i.e. 3-AFC) ascending concentration.

Measure: Oleic Acid Detection Level

Time: Ranges from 5 days after screening to several weeks, pending availablity of participant.

Description: We will measure triolein detection levels as a marker of subjects' ability to detect triglyceride. Triolein taste detection thresholds were separately assessed using a three-alternative forced-choice (i.e. 3-AFC) ascending concentration.

Measure: Triolein Detection

Time: Ranges from 5 days after screening to several weeks, pending availablity of participant.

2 Effect of Polymorphisms in CD36 and STAT3 Genes on Different Dietary Interventions Among Patients With Coronary Artery Disease: a Randomized Clinical Trial With a Nutrigenetic Approach

Background: Cardiovascular diseases are the major health problem worldwide and the understanding of genetic contributions on the development of cardiovascular diseases is increasing significantly. The CD36 is a protein associated with uptake of oxidized forms of LDL and the single nucleotide polymorphism (SNP) rs1761667 A/G in the CD36 gene is correlated with increased consumption of total fat. The transcription factor STAT3 is released during the inflammatory acute phase response and the SNP rs8069645 G/A in the STAT3 gene is associated with abdominal obesity and higher intake of saturated fat. Studies have been shown the benefits of the Mediterranean diet in secondary prevention of cardiovascular disease and these dietary patterns have been often studied with nutrigenetic approach; these studies, however, are often limited to European populations, making it difficult to generalize to different populations. Hypothesis: Different dietary approaches may similarly influence in modifying metabolic, inflammatory and anthropometric profile, especially among patients with coronary arterial disease (CAD). The genetic interaction with environmental factors such as the nutrient intake, and the prescription of a different diet according to individual genotype, could influence the development and/or the treatment of cardiovascular diseases. Objective: To evaluate the effect of three dietary approaches on metabolic, inflammatory and anthropometric profile in patients with CAD and possible interactions with polymorphisms in CD36 and STAT3 genes.

NCT02202265 Coronary Artery Disease Dietary Supplement: Olive oil Dietary Supplement: Nuts Dietary Supplement: Control diet
MeSH: Coronary Artery Disease Myocardial Ischemia Coronary Disease
HPO: Coronary artery atherosclerosis

The CD36 is a protein associated with uptake of oxidized forms of LDL and the single nucleotide polymorphism (SNP) rs1761667 A/G in the CD36 gene is correlated with increased consumption of total fat.

Primary Outcomes

Description: LDL-cholesterol, in mg/dL

Measure: LDL

Time: twelve weeks

Secondary Outcomes

Description: total cholesterol (TC), in mg/dL)

Measure: TC

Time: twelve weeks

Description: non-HDL-cholesterol, in mg/dL

Measure: NHDL

Time: twelve weeks

Description: HDL-cholesterol, in mg/dL

Measure: HDL

Time: twelve weeks

Description: serum triglyceride, in mg/dL

Measure: TG

Time: twelve weeks

Description: glycated hemoglobin (HbA1C), in %

Measure: HbA1C

Time: twelve weeks

Description: fasting glucose, in mg/dL

Measure: FG

Time: twelve weeks

Description: serum insulin, in UI/mL

Measure: Insulin

Time: twelve weeks

Description: Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), calculated according to fasting insulin (microU/L) x fasting glucose (nmol/L)/22.5

Measure: HOMA-IR

Time: twelve weeks

Description: CRP-us, in mg/dL; IL-6, in mg/dL; IL-10, in mg/dL

Measure: inflammatory profile

Time: twelve weeks

Description: body weight, in kg;

Measure: BW

Time: twelve weeks

Description: body mass index (BMI), in kg/m2, calculated according to weight (kg)/height*height (m)

Measure: BMI

Time: twelve weeks

Description: waist circumference, in cm

Measure: WC

Time: twelve weeks

Description: plasma fatty acids, in %

Measure: PFA

Time: twelve weeks

3 The Relationship Between Genetics, Body Mass Index, Fat Intake, Fat Taste Sensitivity and Food Preference

A cross-sectional quantitative study will be carried out; recruiting female, Caucasian participants aged 18-65 years. The relevance of candidate gene studies is disputed. Research has shown associations between genotype and total fat intake. However, food preference is often described as a result of exposure to food types during upbringing. Many single nucleotide polymorphisms (SNP) have been associated with fat taste sensitivity, the majority of research shows that with a reduced sensitivity comes a higher total fat consumption. This study aims to assess the relationship between rs1761667 genotype, body mass index, fat intake, fat taste sensitivity and fat taste preference.

NCT03666182 Obesity Taste Sensitivity Other: No Intervention
MeSH: Hypersensitivity
HPO: Allergy

This study aims to assess the relationship between rs1761667 genotype, body mass index, fat intake, fat taste sensitivity and fat taste preference.

Primary Outcomes

Measure: Body Mass Index

Time: September - November 2018


HPO Nodes


Allergy
Genes 21
CHD1 TGM5 ADA PLA2G7 MTOR FOXP3 PGM3 CARMIL2 SIK3 CCDC28B BBS1 NRXN1 IL4R COX4I2 MS4A2 PLCG2 SPINK5 CSTA CNTNAP2 RBM8A PGM3
Obesity
Genes 465
PDE6A IDH3A ALG13 CANT1 PRKAR1A WDR34 PCARE EIF2S3 RP1 CTSH RAI1 LZTFL1 MTFMT TTC8 PPARG ANOS1 IQSEC2 IQSEC2 C8ORF37 TMEM67 RNPC3 MKRN3 FLRT3 MYT1L SNRNP200 BBS4 IFT172 CEP19 PROKR2 EMD EYS SLC25A4 LEPR KIDINS220 THOC2 PCSK1 PRPF4 ARL6 USP9X RDH12 IGF1 IFT172 ARL3 SOX10 PDE11A FGFR3 NR2E3 CUL4B RAB23 PAX6 ARL2BP DYRK1B GNAS PRPF31 PNPLA6 PRCD RLBP1 FTO KLF11 TBX1 BLK INPP5E HIRA CYP7A1 TMEM43 DHDDS BBS5 MLXIPL LEP CLIP2 WNT4 IFT140 RP2 REEP6 EP300 FHL1 PDE4D SH2B1 CNGA1 CNNM2 PAK3 TNFSF4 IQSEC2 SDCCAG8 MOG TRAPPC9 SDC3 HLA-DQB1 TBL2 POMC ALMS1 PTCHD1 PRPH2 PSMD12 SH3KBP1 SNORD115-1 HSD11B1 ARVCF PRPF8 POMC GUCA1B ATRX SEC24C POMGNT1 ZNF365 SUFU ARMC5 CLCN4 HACE1 RBMX KIAA1549 SLC9A7 SH2B1 IFT27 GNAS EIF2S3 JMJD1C FGF17 COMT MKS1 ZNF81 HERC2 SKI CYP19A1 MKKS SOX2 SLC7A7 GTF2I AKT2 MID2 SIM1 SMARCB1 DNMT3A ENPP1 PRPF6 ZNF408 PRDM16 FGFR1 PROM1 ERMARD BBS10 AIP NPAP1 BEST1 GATA4 BBS1 TUB P4HTM TBX3 KMT2A BBS7 GABRD GP1BB WDR11 RP9 GNAS XRCC4 PAX6 SDCCAG8 RBP3 ADRB3 GNAS PAX4 NSMF NPHP1 RAI1 ATP6AP2 GNAS-AS1 USP8 MAK KCNJ18 CCDC141 IMPDH1 PDSS1 NIPBL ADNP DPYD SETD2 NR0B2 MED12 NDN FAM161A HESX1 NRL BBS10 GHRL DUSP6 LAS1L MKKS P2RY11 BBS5 MEGF8 ZNF711 RREB1 H6PD HESX1 SIN3A CNKSR2 KIDINS220 BBS12 FRMPD4 IFT74 TRIM32 BLK AFF4 POGZ ALB GABRA3 TSPAN7 SLC10A7 SYNE2 CREBBP GNAS RPS6KA3 OFD1 IFT172 APC2 PRKAR1A RPGR BBS9 SNORD116-1 IL1RAPL1 OTX2 NSD1 HACE1 PCSK1 FGFR1 SETD2 BAZ1B EHMT1 ZNF41 INS PROK2 POU3F4 IFT88 PDE6B GNAS ABCC8 RGR ARL13B KMT2D GHR GNAS NEK2 RFC2 CA4 LIPE RERE MAPK8IP3 RHO SCAPER BPTF RAP1A DLG3 BBS9 PCNT LEP IGFALS CRB1 RPS6KA3 TBX1 NEUROD1 CEP164 GTF2IRD1 SIM1 MECP2 ARX SMC3 PHIP TRIP12 CARTPT NTRK2 HDAC8 AGTR2 SEMA3A BRAF AHR PWRN1 OFD1 SETD5 ADNP LZTFL1 PROK2 KISS1R CEP290 HS6ST1 CDHR1 DEAF1 MAN1B1 RAP1B CTNNB1 USP8 BBS2 GCK UPF3B ELN MAN1B1 PTEN TRIM32 MKS1 ROM1 BBS2 LEPR KCNJ11 MRAP2 PRPF3 PDGFB LRAT TRAF3IP1 HDAC8 SPRY4 ELN SRY FEZF1 VPS13B TACR3 KIF7 TAF1 RAB23 FOXP1 HDAC8 CERKL CLRN1 AGRP BBS2 MOG TOPORS ARNT2 ARHGEF6 FMR1 USP27X SHANK3 XYLT1 VPS13B SMAD4 UFD1 EGF UCP3 BBS12 IFT172 SNRPN CACNA1S USH2A HNF1A ACADVL ADRB2 MEGF8 C8ORF37 APOE WDPCP IGF1R CCDC141 NIN IPW MAGEL2 GDI1 NF2 HGSNAT ARL6 HUWE1 SEMA4A EHMT1 SYP IDH3B PRMT7 CEP290 PCNT SH2B1 HDAC4 ADCY3 TTC8 CHD7 AKT2 ABCA4 LMNA HCRT MC4R DMD ZNF513 CRX SYNE1 XYLT1 BDNF TBX3 MC3R KLHL7 DCC SPG11 TTC8 POMC ALMS1 FTSJ1 PDX1 KDM6A LIMK1 BBIP1 BBS7 RPE65 CCDC28B EXOC6B BBIP1 AHI1 ARMC5 AGBL5 PDE4D TULP1 SMC1A DHX38 CEL ARL6 MAGEL2 PROKR2 HLA-DRB1 MKRN3-AS1 SHOX RAD21 IMPG2 ZNF711 C8ORF37 IFT27 PWAR1 PNKP FGF8 HNF4A CDH23 BBS1 WT1 GNAS MTTP ZBTB20 KIZ APPL1 FLII IL17RD SPATA7 MERTK TCF20 MECP2 CXORF56 LMNA BBS4 SLC7A14 SOX3 MC4R LAS1L KCNAB2 CUL4B PDE6G ARHGEF18 SAG RAB39B STX16 UBE3A ACSL4 TBX1 MCM3AP TUB ATRX FSCN2 PHF6 TRAPPC9 PHF6 WT1 CNGB1 HCFC1
Coronary artery atherosclerosis
Genes 48
LMNA LDLRAP1 LDLR ACTA2 CYP7A1 FBN1 APOE APOB ESR1 MAT2A ABCA1 KCNJ5 ABCG8 MYH11 ZNF687 TGFB2 LMNA LMNA ELN LMNA LIPC PPARG LMNA FOXE3 SERPIND1 SMAD4 TGFBR2 SMPD1 MFAP5 ABCA1 APOB LMNA LOX SMAD3 MYH11 MYH11 LOX LMNA PCSK9 ACTA2 ABCG8 ZMPSTE24 TGFB3 PRKG1 TGFBR1 MYLK CEP19 ABCG5