Cohort profile: Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO).
Evelyn Xiu Ling LooShu-E SohSee Ling LoySharon NgMya Thway TintShiao-Yng ChanJonathan Yinhao HuangFabian YapKok Hian TanBernard S M ChernHeng Hao TanMichael J MeaneyNeerja KarnaniKeith M GodfreyYung Seng LeeJerry Kok Yen ChanPeter D GluckmanYap-Seng ChongLynette Pei-Chi ShekJohan G Erikssonnull nullAiru ChiaAnna Magdalena FogelAnne Eng Neo GohAnne Hin Yee ChuAnne Rifkin-GraboiAnqi QiuBee Wah LeeBobby Kyungbeom CheonCandida VazChristiani Jeyakumar HenryCiaran Gerard FordeClaudia ChiDawn Xin Ping KohDesiree Y PhuaDoris Ngiuk Lan LohElaine Phaik Ling QuahElizabeth Huiwen ThamEvelyn Chung Ning LawFaidon MagkosFalk Mueller-RiemenschneiderGeorge Seow Heong YeoHannah Ee Juen YongHelen Yu ChenHeng Hao TanHong PanHugo P S van BeverHui Min TanIzzuddin Bin Mohd ArisJeannie TayJerry Kok Yen ChanJia XuJoanne Su-Yin YoongJohan Gunnar ErikssonJonathan Tze Liang ChooJonathan Y BernardJonathan Yinhao HuangJun Shi LaiKaren Mei Ling TanKeith M GodfreyKenneth Yung Chiang KwekKeri McCrickerdKothandaraman NarasimhanKok Wee ChongKuan Jin LeeLi ChenLieng Hsi LingLing-Wei ChenLourdes Mary DanielLynette Pei-Chi ShekMarielle V FortierMary Foong-Fong ChongMei Chien ChuaMelvin Khee-Shing LeowMichelle Zhi Ling KeeMin GongMya Thway TintNavin MichaelNgee LekOon Hoe TeohPriti MishraQueenie Ling Jun LiSambasivam Sendhil VelanSeng Bin AngShirong CaiSi Hui GohSok Bee LimStella TsotsiStephen Chin-Ying HsuSue-Anne Ee Shiow TohSuresh Anand SadananthanTeng Hong TanTong Wei YewVarsha GuptaVictor Samuel RajaduraiWee Meng HanWei Wei PangWen Lun YuanYanan ZhuYin Bun CheungYiong Huak ChanZai Ru ChengPublished in: European journal of epidemiology (2020)
The Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO) is a preconception, longitudinal cohort study that aims to study the effects of nutrition, lifestyle, and maternal mood prior to and during pregnancy on the epigenome of the offspring and clinically important outcomes including duration of gestation, fetal growth, metabolic and neural phenotypes in the offspring. Between February 2015 and October 2017, the S-PRESTO study recruited 1039 Chinese, Malay or Indian (or any combinations thereof) women aged 18-45 years and who intended to get pregnant and deliver in Singapore, resulting in 1032 unique participants and 373 children born in the cohort. The participants were followed up for 3 visits during the preconception phase and censored at 12 months of follow up if pregnancy was not achieved (N = 557 censored). Women who successfully conceived (N = 475) were characterised at gestational weeks 6-8, 11-13, 18-21, 24-26, 27-28 and 34-36. Follow up of their index offspring (N = 373 singletons) is on-going at birth, 1, 3 and 6 weeks, 3, 6, 12, 18, 24 and 36 months and beyond. Women are also being followed up post-delivery. Data is collected via interviewer-administered questionnaires, metabolic imaging (magnetic resonance imaging), standardized anthropometric measurements and collection of diverse specimens, i.e. blood, urine, buccal smear, stool, skin tapes, epithelial swabs at numerous timepoints. S-PRESTO has extensive repeated data collected which include genetic and epigenetic sampling from preconception which is unique in mother-offspring epidemiological cohorts. This enables prospective assessment of a wide array of potential determinants of future health outcomes in women from preconception to post-delivery and in their offspring across the earliest development from embryonic stages into early childhood. In addition, the S-PRESTO study draws from the three major Asian ethnic groups that represent 50% of the global population, increasing the relevance of its findings to global efforts to address non-communicable diseases.
Keyphrases
- pregnancy outcomes
- magnetic resonance imaging
- high fat diet
- gestational age
- mental health
- type diabetes
- birth weight
- dna methylation
- metabolic syndrome
- physical activity
- cardiovascular disease
- high resolution
- young adults
- bipolar disorder
- machine learning
- mycobacterium tuberculosis
- body mass index
- mass spectrometry
- risk assessment
- depressive symptoms
- big data
- preterm birth
- data analysis
- deep learning
- quality improvement
- sleep quality
- low birth weight
- contrast enhanced
- human health