Population history and genome wide association studies of birth weight in a native high altitude Ladakhi population.
Sushil BhandariPadma DolmaMitali MukerjiBhavana PrasherHugh MontgomeryDalvir KularVandana JainVatsla DadhwalDavid J WilliamsAniket BhattacharyaaEdmund GilbertGianpiero L CavalleriSara L HillmanPublished in: PloS one (2022)
Pathological low birth weight due to fetal growth restriction (FGR) is an important predictor of adverse obstetric and neonatal outcomes. It is more common amongst native lowlanders when gestating in the hypoxic environment of high altitude, whilst populations who have resided at high altitude for many generations are relatively protected. Genetic study of pregnant populations at high altitude permits exploration of the role of hypoxia in FGR pathogenesis, and perhaps of FGR pathogenesis more broadly. We studied the umbilical cord blood DNA of 316 neonates born to pregnant women managed at the Sonam Norboo Memorial Hospital, Ladakh (altitude 3540m) between February 2017 and January 2019. Principal component, admixture and genome wide association studies (GWAS) were applied to dense single nucleotide polymorphism (SNP) genetic data, to explore ancestry and genetic predictors of low birth weight. Our findings support Tibetan ancestry in the Ladakhi population, with subsequent admixture with neighboring Indo-Aryan populations. Fetal growth protection was evident in Ladakhi neonates. Although no variants achieved genome wide significance, we observed nominal association of seven variants across genes (ZBTB38, ZFP36L2, HMGA2, CDKAL1, PLCG1) previously associated with birthweight.
Keyphrases
- low birth weight
- genome wide
- genome wide association
- preterm infants
- copy number
- preterm birth
- human milk
- pregnant women
- gestational age
- birth weight
- dna methylation
- umbilical cord
- mesenchymal stem cells
- healthcare
- genetic diversity
- weight gain
- type diabetes
- endothelial cells
- gene expression
- electronic health record
- adipose tissue
- adverse drug
- big data
- machine learning
- body mass index
- single molecule
- transcription factor
- physical activity
- bone marrow
- deep learning
- skeletal muscle
- drug induced