Birth weight is defined as the first weight of a baby, measured just after it is born and it is of special interest to clinicians, because the higher mortality at both extremes of the weight scale makes it difficult for clinicians to select an optimum birthweight (Mather, 1973). Also, the extremes of birth weight are associated with high risks of perinatal morbidity and mortality (Battaglia 1967, Acker 1967).
Foetal weight and size at the time of birth also represent an interesting trade-off between the offspring’s interest in fuller development in utero and the maternal interest in a producing smaller baby to avoid death in childbirth. Smaller sizes of babies are more likely to experience short or long term health problems and will require specialized care after birth.
DEFINITION OF DISEASE
The World Health Organization divides the range of birth weight in three categories. A birth weight of 2,499 g (5.5 pounds) or less in an infant regardless of gestational age is termed as Low Birth Weight (LBW) as a birth weight of an infant of 2,499 g (5.5 pounds) or less, regardless of gestational age.
FIGURE 1 WEIGHT PER GESTATIONAL WEEK CHARACTERIZATION
Subcategories of this include Very Low Birth Weight (VLBW), which is less than 1500 g (3 pounds 5 ounces), and extremely Low Birth Weight (ELBW), which is less than 1000 g (2 pounds 3 ounces). Normal Weight at term delivery is 2500–4200 g (5 pounds 8 ounces – 9 pounds 4 ounces). Finally, High Birth Weight (HBW) is considered any measurement bigger than normal weight.
In a report by the Office for National Statistics in 2016, about 7% of babies who are born in the UK have a low birth weight. This figure seems to be close to that reported by the National Center for Health Statistics in the U.S . Also, 1.4% of newborns in the US weighed less than 1,500 grams (VLBW).
FIGURE 2 NUMBER OF LIVE BIRTHS WEIGHING LESS THAN 2500 GRAMSB AS A PROPORTION (%) OF TOTAL LIVE BIRTHS
The above figure shows the percentage of LBW infants in the EU region, where we can see that the proportions fall below 10%. In general these figure vary by country and continent but the great majority of low birth weight births occur in low and middle income countries, especially in the most vulnerable populations (Kim 2013, Muglia 2010).
Regional estimates of LBW include 28% in south Asia, 13% in sub-Saharan Africa and 9% in Latin America. Nevertheless, low birth weight is a global concern, as some high-income countries are also faced with high rates for their contexts (e.g. Spain, the United Kingdom of Great Britain and Northern Ireland [UK] and the United States of America [USA]) (March of Dimes,2014).
DESCRIPTION OF LOW BIRTH WEIGHT
There are a plethora of risk factors attributed to mothers and may contribute to LBW such as young age of the mother, multiple pregnancies (because they are often born early, and don't have as much room to grow in the uterus (womb) as single babies), previous LBW infants, poor nutrition, heart disease or hypertension, untreated coeliac disease, drug addiction, alcohol abuse, and insufficient prenatal care.
Apart from previous conditions there can be factors relating to the birth itself, such as problems with the placenta such as pre-eclampsia, which reduces blood flow to the baby.
Moreover, environmental risk factors are also suspect to contribute, such as smoking, lead exposure, and other types of air pollutions.(Umm.edu. 2008-10-22, Tersigni 2014, Saccone 2015). A correlation between maternal exposure to carbon monoxide (CO ) and low birth weight has been reported and the effect on birth weight of increased ambient CO was as large as the effect of the mother smoking a pack of cigarettes per day during pregnancy. (Lewtas 2007). Mercury is a known toxic heavy metal that can harm fetal growth and health, and there has been evidence showing that exposure to mercury via consumption of large oily fish) during pregnancy may be related to higher risks of LBW in the offspring (Gochfeld 2005)
How LBW affects the infant varies in cases. Some low birth weight babies may be more at risk for certain health problems. Some may become sick in the first days of life or develop infections. Others may suffer from longer-term problems such as delayed motor and social development or learning disabilities. An example of these are the following :
• Breathing problems, called respiratory distress syndrome (RDS).
• An increased risk of infection.
• Low blood sugar (hypoglycaemia), and problems with feeding.
• Difficulty with keeping warm.
• Too many red blood cells, which can make their blood too thick (polycythaemia).
• future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease (Barker 2004)
Brown et al in 2002 showed that maternal weight gain was affecting the newborn’s weight. More specifically, in the first and second trimesters a 1kg weight gain in the first trimester predicted a 31g increase in newborn weight (p < 0.0007) and a 1kg weight gain in the second trimester predicted a 26g increase in newborn weight (p < 0.007), but weight gain in the third trimester did not.
Another risk associated with LBW seems to be the birth weights of parents themselves (Magnus et al, 2001). The birth weight correlations reported were 0.226 for mother-child, 0.126 for father-child and the relative risk of low birth weight in the first born child was 8.2 if both parents were low birth weight themselves. That would mean that first born children were almost 8 times more likely to be born with low weight if both their parents were born with low weight.
Another report (Whitfield et al, 2001) calculated also that the correlations between twins were high (monozygotic, r = 0.77 and dizygotic, r = 0.67) leading to substantial estimates of shared environmental effects (56% of variance) with significant additive genetic (23%) and non-shared environmental (21%) components.
Also, they reported the correlation between birth weight and BMI, linking heavier babies to becoming obese adults. A bivariate model of birthweight and adult BMI showed significant positive genetic (r = 0.16, p = 0.005) and environmental (r = 0.08, p = 0.000011) correlations.
GENETIC EPIDEMIOLOGICAL EXAMINATION
Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood (Godfrey et al,2000). Efforts to locate and identify genes controlling human traits, such as birth weight, are usually done on a gene-to-gene basis, without knowing the chances of success in advance.
Both intergenerational studies and studies on offspring of twins have described familial correlations in birth weight and fetal growth, as well as in gestational age at birth (3–11). These findings are thought to be explained by fetal genes passed on from the father and the mother to the fetus and by maternal genes acting on the mother's capability of carrying a pregnancy, but could also be attributed to shared environmental factors between relatives.
Magnus (1984 a,b) and Clausson et al. (2000) have described estimates of heritability in birth weight by use of data on offspring of twins. Magnus (4) found that 50% of the variability in birth weight could be explained by fetal genes, whereas Clausson et al. (2000) estimated heritability to be around 40%. More recently, Magnus et al. (2001) used mother–father–first child trios and concluded that, under the assumption of no cultural transmission on the paternal side, estimates of heritability in birth weight were 25%.
Clausson et al. (2000) also estimated the heritability of gestational age to be around 30 percent. Earlier data from the 1958 British birth cohort showed that both maternal and paternal gestational ages had independent effects on term offspring's gestational age (Hennessy 1998).
Previous genome-wide association studies of birth weight had identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits (Freathy 2010). They found that the 9% of Europeans carrying four birth weight–lowering alleles were, on average, 113g (95% CI 89–137g) lighter at birth than the 24% with zero or one alleles (ptrend = 7 × 10−30). They also stated that the impact on birth weight is similar to that of a mother smoking 4–5 cigarettes per day in the third trimester of pregnancy (Bernstein 2005).
In an expanded genome-wide association meta- analysis and follow-up study of birth weight in up to 69,308 individuals of European descent from 43 studies, researchers (Horikoshi et al, 2013) have extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking.
FIGURE 3 BOX PLOT SHOWING THE PERCENTAGE VARIANCE IN BIRTH WEIGHT EXPLAINED BY FIVE RELATED CHARACTERISTICS
Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height.
Testing the hypothesis that maternal genotype was affecting birthweight is an interesting concept since throughout the cellular processes of gametogenesis and fertilization, fetal genotype is correlated with maternal genotype (r ≈ 0.5). So the researchers used up to 11,307 mother-child pairs from a subset of studies, found no evidence that the 7 associations that were observed at p < 5 × 10−8 were driven by the maternal rather than the fetal genotype.
Associations between fetal genotype and BW could result from indirect effects of the maternal genotype influencing BW via the intrauterine environment, given the correlation (R ≈ 0.5) between maternal and fetal genotype.
Exploring how these variants had associations with birth weight in non-European populations they observed that the 7 SNPs previously found, explained. between 0.32% and 1.52% of the variance in birth weight, which was similar to that of the percentage explained in Europeans in individuals of Middle Eastern, East and Southeast Asian and African origin (total n = 11,848).
FIGURE 4 ASSOCIATION P VCALUES FOR BIRTH WEIGHT FROM THE DISCOVERY META-ANALYSIS
Horikoshi et al in 2016 found 60 regions in the genome that affect birth weight, accounting for around 2% of the variation in birth weight between babies. (p < 5 × 10-8) They combined GWAS data for BW from 153,781 individuals representing multiple ancestries from 37 studies across three components:
i. 75,891 individuals of European ancestry from 30 studies;
ii. 67,786 individuals of European ancestry from the UK Biobank
iii. 10,104 individuals of diverse ancestries (African American, Chinese, Filipino, Surinamese, Turkish and Moroccan) from six studies.
Further analysis, however, revealed a greater number of genetic variations that affect birth weight, but to a smaller degree than those within the 60 key regions. That leads the birth weight variation caused by the baby’s genes at around 15%.
The results revealed that the risk of high blood pressure, type 2 diabetes and coronary artery disease were genetically linked to a low birth weight, whereas a higher birth weight was linked to traits including birth length, greater waist circumference and adult height.
The strong inverse genetic correlations between BW and systolic blood pressure (SBP) that were found were Rg = −0.22, p = 5.5 × 10−13, for Type 2 Diabetes Rg = −0.27, p = 1.1 × 10−6 and for coronary artery disease Rg = −0.30, p = 6.5 × 10−9.
In the figure below is the shared genetic contribution and other major health problems calculated using linkage-disequilibrium score regression. There can be seen strong positive genetic correlations with anthropometric and obesity-related traits including birth length (Rg = 0.81, p = 2.0 × 10−44) and, in adults, height (Rg = 0.41, p = 4.8 × 10−52), waist circumference (Rg = 0.18, p = 3.9 × 10−10) and BMI (Rg = 0.11, p = 7.3 × 10−6).
FIGURE 5 GENETIC CORRELATION (RG) AND CORRESPONDING S.E. BETWEEN BW AND THE TRAITS DISPLAYED
Most studies report a linear inverse association throughout the birth weight distribution, whereby lower birth weight is associated with higher adult SBP. There is also evidence that birth weights at the high end of the distribution are associated with higher SBP. (Gamborg 2007)
Conclusion
The main focus of literature is focused on low birth weight, determinants of it, how it affects the infant and the impact it has on its progressing life. From reading the relevant literature it was found that there are several risk factors affecting birth weight, ranging from the health and lifestyle of the mother before the gestational period, the specific characteristics of the pregnancy and health during pregnancy. It showed significant correlations to the gained weight of the mother and also to the birth weight of the parents themselves.
From a genetic perspective following the results from genome wide association studies and meta analyses of those, researchers were able to improve the variation in birth weight explained by genes from 1% to approximately 15%. They presented also that the genetic variants that were found were also shared with other major health problems.