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 Table of Contents  
ORIGINAL ARTICLE
Year : 2017  |  Volume : 16  |  Issue : 2  |  Page : 103-110

Relationship of second-to-fourth digit ratio with metabolic syndrome indices and serum biomarkers in Hausa ethnic group of Kano, Nigeria


1 Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, Bayero University, Kano, Kano State, Nigeria
2 Department of Human Anatomy, Faculty of Medicine, Ahmadu Bello University, Zaria, Nigeria
3 Department of Chemical Pathology, Faculty of Medicine, Ahmadu Bello University, Zaria, Nigeria

Date of Web Publication4-Jun-2018

Correspondence Address:
Dr. Abdullahi Yusuf Asuku
Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, Bayero University, Kano, P. M. B. 3011, Kano State
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jeca.jeca_24_17

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  Abstract 


BACKGROUND: High prevalence levels of the metabolic syndrome (MetS) in developed and developing countries and the associated high mortality and morbidity are forcing scientists to explore promising therapeutic agents and population-specific anthropometric criteria for defining its phenotype.
OBJECTIVES: The aim of this study is to investigate the relationship between digit length and second-to-fourth digit ratio (2D:4D) with the indices of MetS and its serum biomarkers.
MATERIAL AND METHODS: The study was a cross-sectional study which included 465 (266 males and 199 females) Hausas of Kano, with a mean age of 34.4 years and 32.0 years for males and females, respectively. Systematic random sampling technique was employed for subject recruitment. Height, weight, waist circumference, body mass index, and digit lengths were obtained using standard protocol. Overnight fasting blood sample was obtained for fasting blood glucose, high density lipoprotein cholesterol (HDL-c), total cholesterol, triglycerides, low-density lipoprotein, uric acid, and adiponectin estimation using standard laboratory protocols. Blood pressure was measured following standard clinical procedure. Pearson's correlation was used to test the association between the digit lengths, 2D:4D with MetS indices, uric acid, and adiponectin. To compare between-group parameters of males and females, left and right hand, Student's t-test and one-way ANOVA were used. SPSS version 20 software was used for statistical analyses and P < 0.05 was set as level of significance.
RESULTS: 2D:4D showed significant positive correlation with uric acid, blood pressure, and serum parameters of MetS. A negative correlation was observed between 2D:4D, adiponectin, and HDL. In both sexes, the R2D:4D had stronger correlation with MetS indicators when compared with the L2D:4D.
CONCLUSION: 2D:4D is good correlate of metabolic risk parameters and R2D:4D correlates better than L2D:4D.

Keywords: Hausa ethnic group, metabolic syndrome, second-to-fourth digit ratio, serum biomarkers


How to cite this article:
Asuku AY, Danborno B, Akuyam SA, Timbuak JA, Adamu LH. Relationship of second-to-fourth digit ratio with metabolic syndrome indices and serum biomarkers in Hausa ethnic group of Kano, Nigeria. J Exp Clin Anat 2017;16:103-10

How to cite this URL:
Asuku AY, Danborno B, Akuyam SA, Timbuak JA, Adamu LH. Relationship of second-to-fourth digit ratio with metabolic syndrome indices and serum biomarkers in Hausa ethnic group of Kano, Nigeria. J Exp Clin Anat [serial online] 2017 [cited 2018 Aug 21];16:103-10. Available from: http://www.jecajournal.org/text.asp?2017/16/2/103/233674




  Introduction Top


The metabolic syndrome (MetS) is a cluster of interrelated common clinical disorders, including hypertension, hyperglycemia, glucose intolerance, and dyslipidemia in addition to obesity (Moller and Kaufman, 2005). It is defined based on the presence of three or more of the following criteria: abdominal obesity with waist circumference (WC) >94 cm for men or >80 cm for women (Grundy et al., 2005), triglycerides (TG) >150 mg/dl, high-density lipoprotein HDL-cholesterol (HDL-C) <40 mg/dl for men or <50 mg/dl for women (Bergman et al., 2006), blood pressure >130/85 mmHg (Tremblay et al., 2004), and fasting glucose >100 mg/dl (Grundy et al., 2005).

Alarmingly, high prevalence levels of the MetS in developed and developing countries and the associated high mortality and morbidity are forcing scientists to explore promising therapeutic agents and population-specific anthropometric criteria for defining its phenotype (Matsuzawa, 2005). The use of anthropometric measurements as screening tools for MetS is well-documented (Akuyam et al., 2009; Lear et al., 2010; Bergman et al., 2011; Oyeyemi et al., 2014; Pinar et al., 2015; and Ravinder and Manju, 2016). There is, however, ethnic/population-specific variation in the validity of the different anthropometric tools (Tulloch-Reid et al., 2003).

Second-to-fourth digit ratio (2D:4D) is a sexually dimorphic anatomic variable that reflects intrauterine androgen exposure (Manning et al., 2002; Oyeyemi et al., 2016). The ratio is currently receiving great attention from investigators having demonstrated significant correlation with important body traits (Manning et al., 1998; Manning et al., 2001; Fink, et al., 2003; Fink, et al., 2006; Danborno et al., 2008; Danborno et al., 2010; and Oyeyemi et al., 2014). Some disease conditions such as autism, depression and developmental psychopathology, congenital adrenal hyperplasia, and polycystic ovarian syndrome have also correlated with digit ratio (Manning et al., 2001; Brown et al., 2002; Okten et al., 2002; Cattrall et al., 2005; and Fink et al., 2007).

The 2D:4D ratio has also been shown to correlate well with anthropometric measures of adiposity. Accordingly, 2D:4D was correlated with neck circumference (NC) among Europeans (Fink et al., 2003; Fink et al., 2006), with WC and hip circumference (HC) among Ugandans (Abba et al., 2012), with NC, WC, HC, CC, body mass index (BMI), waist-to-height ratio among Nigerians (Danborno et al., 2008; Oyeyemi et al., 2016). The correlation of 2D:4D with birth weight as demonstrated by Danborno et al., (2010) also strengthens the likelihood of an association between 24:4D and MetS since low birth weight has been shown to be an important predictor of hypertension, diabetes, and obesity in adulthood (Barker 1998; Huxley et al., 2000; and Anazawa et al., 2003). Globally, there is a paucity of data on the relationship between 2D:4D and the actual indices of MetS. This study is therefore conducted to investigate the relationship of 2D:4D with components of MetS, adiponectin, and uric acid which are biomarkers of MetS.


  Materials and Methods Top


Systematic random sampling technique was employed in selecting 465 original Hausas of Kano based on a history of at least two parental generation being Hausas from Kano. Participants were recruited from outpatient units of Murtala Muhammad specialist Hospital, Khadija Memorial Hospital, SU clinic, General Hospital Dawakin-Tofa and the old campus of Bayero University, Kano. The study included only subjects in the age range of 18–68 years. Subjects with pregnancy, abdominal or pelvic space occupying lesions, congenital and/or acquired spinal or digit deformity were, however, excluded from the study. Subjects that were on medications that could interfere with any component of MetS were also excluded from the study. Ethical approval was obtained from Kano state hospitals management board and written informed consent obtained from the subjects.

Height was measured to the nearest 0.1 cm as the vertical distance between the standing surface and the vertex of the head while the subject was standing erect in the frank forth plane and without shoes using a stadiometer. The weight was measured in kilograms using a digital weighing scale while the subject is in light clothes. The BMI was calculated by dividing the weight in kilograms by the square of the height in meters and the result expressed in kg/m 2. WC was measured in centimeter with a nonstretchable plastic tape horizontally placed over the unclothed abdomen at the narrowest point between the lowest rib and the iliac crest.

Digit lengths [Figure 1] were measured on the ventral surface of the hand from the basal crease of the digit to the tip of the finger using a digitals caliper (MicroMax, USA) measuring to 0.01 mm and reported on questionnaire. This technique of measuring digit length has been reported to have high degree of repeatability (Manning et al., 1998; Danborno and Danborno, 2015).
Figure 1: Measurement of digit length

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A mercury sphygmomanometer was used for measuring blood pressure. Two measurements were taken, and at least, 2 min was allowed between readings. While the diastolic reading was taken at the level when sounds disappear (Korotkoff phase V), the systolic was taken at the level when it appears. The brachial artery was the site of auscultation. Subjects were asked to refrain from smoking or ingesting caffeine for 30 min before measurement, and the measurement was taken after at least 5 min of rest (Haffner et al., 2005).

For the estimation of serum total cholesterol (TC), TG, low-density lipoprotein (LDL) and HDL-C, fasting blood glucose (FBG), uric acid, and adiponectin, blood specimen was collected from 161 of the subjects after 10–12 h of fasting through superficial veins of the upper limb. From each selected subject, 5 ml of venous blood sample was collected using a sterile 21G needle fitted with syringe. Blood collection was done during the morning hours to avoid the effect of diurnal variation or circadian rhythm in the blood parameters to be measured. Standard technique of venipuncture and universal safety precaution was employed. Blood sample was transferred into a plain blood specimen bottle and allowed to stand until it was properly clotted. The blood samples were preserved in an ice pack insulating container to preserve the temperature and then transported to the laboratory immediately after each exercise of sample collection. Sample was then centrifuged at 300 rpm for 5 min after which serum was separated and immediately used for analysis.

Serum glucose was measured using the enzymatic method of Trinder (1969). Three test tubes were labeled blank, standard and test, then 1 ml of glucose reagent was placed into each. Into the test tubes, 10 μl of distil water, standard solution, and test serum was added to the test tubes, respectively. These was then mixed and incubated at 37°C for 10 min, after which the absorbance (optical density) of the test solution and standard was read at 505 nm using the blank solution to zero the spectrophotometer.

The result was calculated as follows:



Where the concentration of the glucose standard is 5.55 mmol/L.

Serum TC, TG, and HDL concentrations were measured using enzymatic method by Wybenga et al., (1970).

For TC and TG, three test tubes were labeled as test, standard, and blank and to each test tube; 1000 μl of the reagent was added. A volume of 10 μl sample was added to test, and 10 μl standard to standard tube and 10 μl distilled water to Blank. It was then mixed well and incubated for 5 min at 37°C or at room temperature for 15 min. Reading was taken at 530 nm and 500 nm for TC and TG, respectively.

The results were calculated as:



Where the concentration of the TC standard is 5.17 mmol/L and that of TG standard is 2.28 mmol/L.

For HDL, in to a clean test tube 0.5 ml serum + 0.5 ml HDL reagent was mixed and allowed to stand for 10 min. It was then centrifuged for 20 min at 2000 rpm or 10 min at 4000 rpm. Cholesterol reagent 1000 μl was dispensed in to three cleaned test tubes labeled blank, standard, and sample. A volume of 50 μl of supernatant was dispensed in to tube sample, 50 μl of stantadard was dispensed into standard tube, and 50 μl dispensed in to the blank tube. All were mixed and incubated at 37°C for 5 min and absorbance was read at 530 nm.

The result was calculated as:



Where the concentration of the TC standard is 5.17 mmol/L.

LDL-cholesterol was calculated from measured values of TC, TG, and HDL-C according to the Friedewald's equation.

LDL-cholesterol = TC-(HDL-C + TG/2.2) mmol/L.

Serum uric acid concentration was measured using Caraway (1955) method: Into a centrifuge tube, 4 ml of water was added, followed by 0.5 ml of the serum, then 0.25 ml of sulfuric acid, 0.25 ml of sodium tungstate. The solution was then mixed and allowed to stand for 5 min and then spanned. Three tubes were then labeled as test, standard, and blank. A volume of 1.5 ml of sample was added to the tube marked-test and 1.5 ml working standard into the tube marked-standard. A volume of 0.5 ml sodium carbonate and 0.5 ml phosphotungstic acid was added to all test tubes, mixed, and allowed to stand for 15 min at room temperature and read at 680–710 nm.

Uric acid concentration was then calculated as:



Serum adiponectin concentration was determined using the Solid-Phase ELISA method (Pischon et al., 2003). First, the sample was pretreated by adding 100ul of protease buffer and 400ul of sample pretreatment buffer to 10 μl of sample and then stirred thoroughly. One milliliter of the dilution buffer will then be added to 10 μl of the pretreated sample and then stirred thoroughly under room temperature. Fifty microliter of each of standard and diluted pretreated samples were added to the appropriate wells. The plates were then covered with a plate sealer and incubated for an hour at room temperature. The plates were decanted and stroked against an absorbent towel to remove excess liquid. Washing was then done by adding 350–400 μl of wash buffer to each well. The wash buffer was decanted and the plate was stroked against absorbent towel to remove residual liquid. This cycle was repeated for a total of three washes. 50ul of biotin-labeled monoclonal antibody was then added to each well. The plate was then covered with a plate sealer and incubated for an hour at room temperature. At this stage, the washing process was repeated and 50ul of the enzyme streptavidin was added to each well and further incubated for 30 min. The third phase of the wash process was then followed immediately. Then, 50 μl of substrate solution was added to each well and incubated for 10 min. Finally, the color intensity or absorbance was measured within 30 min using a microplate reader set to 492 nm.

The data were expressed as mean ± standard deviations, minimum, and maximum as descriptive statistics. Pearson's correlation was employed to determine the relationships between variables in the study. SPSS version 20 (IBM Corporation, NY, USA) software was used for statistical analyses and P < 0.05 was set as level of significance.


  Results Top


[Table 1] and [Table 2] shows the mean, standard deviation, minimum and maximum age, height, weight, of the digit length, digit ratio, blood pressure, serum parameters of MetS, uric acid, and adiponectin.
Table 1: Description of digit length, digit ratio and blood pressure of study participants

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Table 2: Description of Serum parameters of metabolic syndrome, uric acid and adiponectin of participants

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From [Table 3], [Table 4], [Table 5], it was observed that 2D:4D showed a significant positive correlation with diastolic blood pressure (DBP), systolic blood pressure (SBP), serum uric acid, FBG, TC, TG and LDL but a negative correlation was observed for adiponectin and HDL. Comparing the correlation coefficients of the 2D:4D of both hands, the R2D:4D showed stronger correlation with BP, MetS biomarkers, FBG, and HDL compared to L2D:4D. In both males and females, 2D:4D correlated with MetS components in a similar pattern of varying strength. Comparison of the correlation of digit ratio with MetS between males and females shows that the R2D:4D in both sexes had similar correlation strength with HDL and FBG. However, its correlation with the serum biomarkers, TC, TG, and LDL was stronger in female subjects. In addition, DBP and SBP correlated better with R2D:4D in males. For the L2D:4D, higher correlation with MetS components were observed in females, except for the pressure components of MetS where the coefficient of correlation was very similar. In each gender, the R2D:4D had higher correlation with MetS indicators when compared with the L2D:4D.
Table 3: Correlation between Digit length and digit ratio with MetS components, adiponectin and uric acid in the general population

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Table 4: Correlation between Digit length and digit ratio with MetS components, adiponectin and uric acid in male participants

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Table 5: Correlation between digit length and digit ratio with MetS components, adiponectin and uric acid in female participants

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  Discussion Top


The idea of finding relationship between digit ratio and MetS is an evolving one. 2D:4D has been reported to correlate with some selected body adiposity measures in the previous studies (Danborno et al., 2008; Abba et al., 2012; and Oyeyemi et al., 2016), therefore, as observed in this study, its correlation with pressure and serum components of MetS which are tightly linked to adiposity (Achie et al., 2012; Marno et al., 2008; Tulloch-Reid et al., 2003; and Mbanya et al., 2015) is not out of scope. 2D:4D relationship with MetS parameters as observed in this study is also validated by its observed strong correlation with serum adiponectin and uric acid which are independent biomarkers that are also sexually dimorphic in their normal mean serum values.

In keeping with this study, in North India, Ravinder and Manju (2016) conducted a cross-sectional observational study on 200 subjects to assess the relationship between digit length and digit ratio with hypertension and revealed a positive and significant correlation. Contrarily, Pınar et al.(2015) recruited 137 female subjects in turkey for a study to assess the relationship of 2D:4D with WC, BP, FBG, HDL, and TG and found no significant association with all these measured parameters. The smaller sample size of the above-cited study could explain the absence of correlation between 2D:4D and the measured MetS parameters. More so that in the same study, it was shown that 2D:4D did not show any correlation with all the anthropometric measures of adiposity which contradicts the vast majority of reports in the body of literature on the subject matter (Fink et al., 2003; Fink et al., 2006; Danborno et al., 2008; Abba et al., 2012; and Oyeyemi et al., 2016).

In addition, the study of Pınar et al.(2015) whose findings are in conflict with this study recruited only female subjects and since 2D:4D has been shown to be sexually dimorphic in measurement and sometimes in relationship with body traits (Fink et al., 2003; Oyeyemi et al., 2016), generalization of such results to both sexes may not be appropriate. Moreover, in the present study, unlike the above-cited study, the validity of the relationship between 2D:4D and MetS components were tested using uric acid and adiponectin as biomarkers. It is also possible that the prevalence of obesity and obesity-related metabolic derangement is low in the population studied by Pınar et al.(2015) and this may possibly affect the likelihood of a significant statistical correlation between 2D:4D and adiposity measures or MetS indices. The World Health Organization (WHO, 2014) has reported that the global prevalence of obesity shows a very wide variation from extremely low in some communities to very high in others. It, therefore, implies that; finding relationships between obesity measures and any other body characteristics in populations with extremely low prevalence may not yield a reliable result. The smaller sample size (137) of the study of Pınar et al.(2015) is another possible reason for the differences observed between the study and the present study, moreover, the study was conducted on a population of different ethnicity and ethnicity has been reported to affect the interrelationship between anthropometric measures and MetS (Lear et al., 2007; Lear et al., 2010; and Katzmarzyk et al., 2011).

Interestingly, this study shows that 2D:4D showed a significant correlation with the actual indices of MetS (serum lipid profile, glycemic level, and blood pressure). This relationship even attracts more attention considering that it also correlated with uric acid and adiponectin, putting emphasis on the probable validity of 2D:4D as a surrogate marker of MetS. It is possible that the pathophysiologic mechanism linking 2D:4D with MetS may be similar to but not exactly the same as those linking body adiposity measures with MetS. For example, it is well established that the susceptibility of an individual to MetS is determined by both modifiable and nonmodifiable factors. While the nonmodifiable factors are mainly genetic and not amenable to environmental influence, the modifiable ones can be influenced by lifestyle. 2D:4D being established in utero and remaining unchanged throughout life (Çelik et al., 2010; Umut et al., 2015), its determinants may similarly constitute a genetic variant having MetS as its manifesting feature in latter life. While the above hypothetical link between 2D:4D and MetS may not be significantly influenced by lifestyle, body adiposity measures even though have some genetic components too, factors such as diet (Paniagua et al., 2007; Romaguera et al., 2009) and physical activity (Van Harmelen et al., 1997; Ross and Janiszewski, 2006) have been shown to significantly influence it.

Furthermore, prenatal androgen level, the major determinant of 2D:4D has been shown to enhance the development of cardiovascular system (English et al., 2000; Pokrywka et al., 2005). Since a high testosterone level will lead to development of a longer ring finger and a lower 2D:4D, this also implies that individuals with lower 2D:4D are likely to have a well-developed cardiovascular system and thus normal cardiovascular function. On the other hand, persons with higher 2D:4D may have a poorly developed cardiovascular system and may be more likely to manifest features of poor cardiovascular function exemplified by systemic hypertension. Inferentially, since BP is a hallmark of cardiovascular function, this may partly explain why 2D:4D was found to correlate with BP as observed in this study and as reported by Ravinder andManju (2016). Further to this, the correlation of 2D:4D with birth weight as demonstrated by Danborno et al., (2010) also strengthens the likelihood of an association between 24:4D and MetS since low birth weight has been shown to be an important predictor of some important component of MetS such as hypertension, diabetes, and obesity in adulthood (Baker 1998; Huxley et al., 2000; Anazawa et al., 2003).

In both males and females, the result of this study indicates that the R2D:4D is a better correlate of MetS indices. The reason for this asymmetry is not very clear, but the development of digit ratio appears to be a function of androgen sensitivity related to X-linked androgen receptor (AR) gene on the digit rather than the androgen concentration (Romano et al., 2006). If the alleles in the AR genes have more CAG, it makes the AR gene insensitive to the testosterone while it is compensated by producing more testosterone in the embryo (Romano et al., 2006). It is possible that these ARs are unevenly distributed with a higher concentration on the right hand. In support of this study, Oyeyemi et al. (2014) reported that the correlation of the right 2D:4D with measures of body adiposity was stronger when compared to the left. This is also in agreement with some previous studies (Hönekopp and Watson 2010; Zhao et al., 2012).

Right-hand 2D:4D is believed to be a better predictor of intrauterine testosterone levels (Manning et al., 1998; Williams et al., 2000; and Hönekopp and Watson2010). Thus, sex difference in the right-hand 2D:4D is more pronounced than that in the left hand. Invariably, the right-hand shows stronger correlation with predicted variables than that the left hand (Manning, 2002). This assertion is, however, not generally agreed on as there are other studies showing the correlation of the left 2D:4D with important biological traits to be stronger than the right 2D:4D. Danborno et al. (2007) reported the left 2D:4D to correlate better with birth weight, a testosterone linked sexually dimorphic feature (Danborno and Afegbua 2006). In addition, the study of Fink et al., (2003) found that BMI was better correlated with the left 2D:4D in males.


  Conclusion Top


2D:4D in males and females correlated significantly with MetS indices, uric acid, and adiponectin. The 2D:4D of the right hand is a better MetS correlate compared to the left 2D:4D in both sexes.[54]

Financial support and sponsorship

This work is an extract of a Ph.D. dissertation which was sponsored by Bayero University Research Grant Unit and Tertiary Education Trust Fund of Nigeria.

Conflicts of interest

There are no conflicts of interest.



 
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