Genetics: locus 10: 21,748,880 - genes MLLT10,

[ME/CFS Science Blog]

Another locus that was just below the significance threshold (p = 6.3 × 10⁻⁷) in DecodeME. The A risk allele of the top hit was present in 29.6% of chromosomes in cases, 28.0% in controls.

The signal seems to point to the gene MLLT10 as most of the credible set lies inside it.


Some of it lies inside DNAJC1 but looking at the Hi-C data and 3D folding, it lies at the edge or outside the domains. It also had less loops in the ENCODE data. Both show the regions that often touch and are connected. FLAMES also think the signal points to MLLT10




In the eqtl data there were some good matches for the non-coding RNA MIR1915HG

Trait (gene)	Study	PP.H4	lead_p	risk_allele
MIR1915HG	GTEx_v10 | brain (cerebellum) | naive | QTD000166	0.96	7.4e-10	raises (z = 5.7)
MLLT10	GTEx_v10 | thyroid | naive | QTD000341	0.93	4.3e-06	raises (z = 4.6)
MIR1915HG	GTEx_v10 | brain (cerebellum) | naive | QTD000161	0.93	1.8e-08	raises (z = 5.2)
MIR1915HG	GTEx_v10 | artery (tibial) | naive | QTD000141	0.91	8.8e-08	raises (z = 4.2)
MIR1915HG	GTEx_v10 | esophagus (muscularis) | naive | QTD000246	0.90	2.8e-06	raises (z = 4.0)
MLLT10 [ILMN_1743538]	Fairfax_2014 | monocyte | naive | QTD000081	0.85	4.8e-07	raises (z = 4.5)
MLLT10	Cytoimmgen_reannotated | CD4+ TCM cell | naive_16H | QTD000914	0.70	7.3e-06	lowers (z = -4.3)
MIR1915HG	GTEx_v10 | adipose | naive | QTD000116	0.66	1.4e-05	raises (z = 3.3)
MLLT10	Alasoo_2018 | macrophage | IFNg_18h+Salmonella_5h | QTD000016	0.64	3.8e-06	lowers (z = -3.9)
MIR1915HG	GTEx_v10 | artery (aorta) | naive | QTD000131	0.60	2.1e-06	raises (z = 3.2)

But then in the phewas there were so many other GWAS traits that almost perfectly colocalized here. It's hard to make sense out of all of these. It made me a bit skeptical about the signal: perhaps it suggests that it's driven by some selection bias in the UK biobank cohort?

Trait	PP.H4	lead_p	study_ID	Source
Fresh fruit consumption	0.99	2.9e-24	ebi-a-GCST90096912	OpenGWAS
Body fat percentage (UKB data field 23099)	0.99	8.3e-24	ebi-a-GCST90013975	OpenGWAS
Waist circumference (UKB data field 48)	0.98	1.9e-24	ebi-a-GCST90014020	OpenGWAS
Salad consumption	0.98	6.7e-16	ebi-a-GCST90096923	OpenGWAS
Monocyte count	0.97	3.0e-11	ebi-a-GCST90018967	OpenGWAS
White blood cell count (monocyte)	0.97	5.0e-12	ebi-a-GCST90028998	OpenGWAS
Medication for pain relief constipation heartburn: Paracetamol	0.97	4.5e-08	ukb-a-455	OpenGWAS
Monocyte count	0.97	4.4e-11	ukb-d-30130_irnt	OpenGWAS
Leg fat percentage (right)	0.97	1.6e-22	ukb-a-274	OpenGWAS
Salad / raw vegetable intake	0.97	1.4e-12	ukb-b-1996	OpenGWAS
Lung function (FVC)	0.96	1.1e-08	ebi-a-GCST007429	OpenGWAS
Adult BMI females	0.95	1.2e-14	ieu-b-5117	OpenGWAS
Weight	0.95	1.2e-15	ukb-a-249	OpenGWAS
Qualifications: College or University degree	0.95	2.5e-07	ukb-a-397	OpenGWAS
Lung function (FVC)	0.95	7.9e-11	ebi-a-GCST90029027	OpenGWAS
IDP dMRI ProbtrackX MO str l	0.95	5.9e-07	ubm-a-705	OpenGWAS
Qualifications: College or University degree	0.94	1.7e-08	ukb-b-16489	OpenGWAS
Physical activity (Total log acceleration 8am-10am)	0.94	1.8e-09	ebi-a-GCST90061413	OpenGWAS
Hip circumference (UKB data field 49)	0.94	3.5e-21	ebi-a-GCST90014021	OpenGWAS
IDP_dMRI_TBSS_ISOVF_Superior_fronto-occipital_fasciculus_L	0.94	9.9e-07	ubm-b-2095	OpenGWAS

 

[ME/CFS Science Blog]

It's hard to make sense out of all of these.

The list is longer than shown in the table. There were 74 datasets that reached PP.H4 > 0.9 and 209 that reached PP.H4 > 0.8, an enormous differences compared to other loci!

The traits are mainly about: adiposity, diet, activity, smoking/education, monocytes, lung function, pain/medication and brain scans.