Effect of low- and high-protein maternal diets during gestation on reproductive outcomes in the rat: a systematic review and meta-analysis

Abstract

Studies with animal models have consistently demonstrated adverse health outcomes in offspring born following nutritional manipulation during gestation. However, the effects of gestational dietary protein modification on reproductive outcomes at birth are less clear. We, therefore, conducted a systematic review and meta-analysis of controlled trials to determine whether high- or low-protein diets are associated with altered reproductive outcomes in a commonly studied species, the rat. Included studies were identified through a systematic search using electronic databases and manual literature review to identify randomized studies published between June 1972 and March 2019. Thirty-two studies were identified and used to analyze the effects of low- and high-protein gestational diets on litter size, litter weight, gestational weight gain, and gestational feed intake. The results indicate that low-protein diets significantly reduced litter weight (P < 0.00001) and gestational weight gain (P < 0.0006), but did not influence litter size (P = 0.62) or gestational feed intake (P = 0.25). In contrast, high-protein diets were found to reduce gestational feed intake (P = 0.004) but did not influence litter size (P = 0.56), litter weight (P = 0.22), or gestational weight gain (P = 0.35). The results suggest that low but not high-protein gestational diets alter reproductive outcomes at birth in rats.

Introduction

Studies with animal models have consistently demonstrated adverse health outcomes in offspring born following suboptimal nutritional programming by dietary manipulation during gestation (Langley-Evans, 2009). Of interest, restricted and excessive nutrition during pregnancy each induces similar adverse outcomes in offspring, including hypertension, glucose intolerance, insulin resistance, and adiposity in a range of mammalian species, including humans, rats, mice, and sheep (Langley-Evans, 2009; Lopes et al., 2017). These findings have attracted considerable interest given the increasing incidence of these disorders in humans.

The effects of maternal protein restriction on nutritional programming have been extensively studied with animal models (Langley-Evans, 2009) and have been reported to cause various metabolic, renal and cardiovascular diseases in both human and animal (Hostetter et al., 1986; King and Levey, 1993; Langley-Evans et al., 1994, 1996; Guzmán et al., 2006; Langley-Evans, 2009). In addition, short-term consumption of low-protein diets by gestating rats resulted in multiple organ and systems compromise, including neonatal heart abnormalities, elevated blood pressure, impaired renal development, and poor growth rate (Langley-Evans, 2009). Animal model studies have also demonstrated that high-protein gestational diets result in adverse health outcomes in offspring (Hallam and Reimer, 2013). However, in contrast to the adverse health outcomes which have been consistently reported in offspring following nutritional manipulation during gestation, the effects of gestational dietary protein modification on reproductive outcomes at birth are less clear.

Animals have physiological regulatory mechanisms to ensure optimal absorption of nutrients to meet their needs (Chambers et al., 1995). Consumption of low dietary protein may increase food intake to compensate for protein needs (Sorensen et al., 2008), increased dietary protein may reduce energy intake in rats (Bensaïd et al., 2003). Such regulatory mechanisms may, therefore, have important effects on the reproductive and health outcomes in offspring born following modification of the protein content of gestational diets.

Our laboratory is interested in early embryo development and how nutrition might modulate this development. There have been a number of studies in mammals including rodents and humans looking at the effects of dietary protein mostly investigating health parameters such as cardiovascular disease with a few investigating reproductive physiology. Many of these studies have contradictory or inconclusive findings and low numbers of subjects which would make identifying subtle effects difficult. Therefore, the purpose of this study was to conduct a systematic review and meta-analysis to clarify the influence of dietary protein during gestation on reproductive outcomes in the rat.

Materials and Methods

Search Strategy

Potential studies were identified by conducting a systematic search using PubMed, www.ncbi.nlm.nih.gov/pubmed to identify randomized studies published between June 1972 March 2019 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method for reporting systematic review and meta-analysis (Moher et al., 2009). The search involved the key concepts of dietary protein interventions to effect change in feed intake, gestational weight gain, litter size, and litter weights. The search terms were combined with sensitive search methods to reveal randomized controlled trials of the effects of varied protein diets in rats. The articles so identified were thoroughly scrutinized for new references. All identified papers, after removal of duplicates, were assessed independently by two reviewers; a third reviewer was consulted to resolve disputes. Hand searches of published papers were also conducted up until March 2019.

Included Studies

We included all studies of dietary trials using rats that examined the effects of low protein (5 to 10%) vs. control (16 to 22%) protein) or high protein (32 to 55%) vs. control (16 to 20%) protein diets fed only during the gestational period. Publication language was not restricted.

Excluded Studies

All review papers and randomized animal studies other than rats were excluded. Interventions that compared dietary protein with other macronutrients, randomized rat studies that compared different types of proteins to those included above, and nonrandomized control studies were excluded. Studies that did not have any of the desired outcome measures (see below) were excluded. Some trials were excluded as a result of the application of the treatments diets outside the gestational period. Also excluded are studies without a control group. Several authors were contacted to provide missing data or to clarify if data were duplicated in multiple publications. Incomplete data, or data from an already included study, were excluded.

Outcome Measures

The following outcome measures were included gestational weight gain, feed intake, litter size, and litter weights.

Studies Included in the Review

The initial search identified 17,261 articles. Careful observation of recent relevant journal articles yielded a further 6 manuscripts. Out of 17,267 studies, 156 duplicates were removed, 15,994 were excluded at first inspection as not relevant to this analysis, 650 were removed after reading titles or abstract, 357 studies were not protein intervention trials, and leaving 111 studies. After thorough examination of the remaining studies, a further 78 were excluded as they did not meet inclusion criteria, leaving 32 studies suitable for inclusion. The PRISMA flow diagram (see Figure S1 in supplementary data file) summarizes the search details.

The diets of all included studies were isocaloric and contained casein as the protein substrate of all included studies. Animals were allocated to the experimental diets on the morning that sperm or a copulatory plug was observed and this was deemed day 1 of pregnancy. Randomization of the rats to experimental groups was reported in most studies but not all; however, as many rat colonies are inbred and many outbred colonies have minimal genetic variation (Brekke et al., 2018), the effect is likely to have been minimal. Rats that failed subsequently to become pregnant were removed from the study.

Data Synthesis

Extracted information was archived in a database and data were recorded in standard (SI) units. The extracted data include authors, year, number of subjects in treatment and control group, and the dietary protein levels. The reproductive outcome data analyzed were the means and SDs of the following variables; litter size (the number of the offspring at birth), litter weight (weight of the individual young at birth), gestational weight gain (average weight gained by the dam during the experimental period), and feed intake (average daily feed consumed during the experimental period).

Statistical Analysis

Meta-analyses were carried out for continuous data by using means and SDs (converted from standard errors where applicable) of outcome measures at end of gestation using Revman 5.3 software (Nordic Cochrane Centre Denmark) to create Forest plots and R v.3.4.2 software for trim-and-fill analyses (R Core Team, 2017). We pooled data using the generic inverse variance method with random and fixed‐effects models and are expressed as mean differences (MDs) at 95% CIs for each study. We assessed heterogeneity between studies using χ ² tests and the I² statistics using the Cochrane Q test according to Higgins et al. (2011). Publication bias was determined using funnel plots, Egger and Begg tests (Egger et al., 1997), and trim-and-fill analyses (Banks et al., 2012).

Results

The experimental details of the 32 included studies are shown in Table 1 (low protein) and Table 2 (high protein).

Table 1.

Experimental design characteristics of the studies comparing effects of low and adequate protein diets

	% protein in diet (number of animals)
Studies	Experimental	Control
Alexandre-Gouabau et al. (2011)	8 (6)	20 (8)
Barros et al. (2018)	8 (14)	17 (8)
Brawley et al. (2003)	8(17)	19 (17)
Cherala et al. (2006) L93 vs. C93	8 (7)	19 (7)
Cherala et al. (2006) LM 96 vs. M96	8 (7)	19 (7)
Cornock et al. (2010)	9 (9)	18 (9)
Courrègesa et al. (2002)	8 (7)	20 (4)
Fernandez-Twinn et al. (2003)	8 (8)	20 (8)
Guzmán et al. (2006)	10 (12)	20 (11)
Langley-Evans and Nwagwu (1998)	9 (15)	18 (14)
Langley-Evans (2000) S18 vs. S9	9 (3)	18 (3)
Langley-Evans (2000) H22 vs. H9	9 (4)	22 (4)
Nwagwu et al. (2000)	9 (7)	18 (8)
Otani et al. (2004)	9 (18)	20 (18)
Qasem et al. (2010)	8 (16)	19 (14)
Ramadan et al. (2013)	5 (10)	20 (10)
Rebelato et al. (2013)	6 (6)	17 (6)
Reyes-Castro et al. (2011)	10 (8)	20 (8)
Reyes-Castro et al. (2012)	10 (16)	20 (16)
Rodriguez-Gonzalez et al. (2012)	10 (20)	20 (20)
Sayer et al. (2001)	9 (4)	18 (5)
Snoeck et al. (1990)	8 (33)	20 (25)
Theys et al. (2009)	8 (7)	20 (7)
Torrens et al. (2003)	9 (9)	18 (12)
Woods et al. (2001)	8.5 (21)	19 (29)
Zambrano et al. (2005)	10 (14)	20 (14)
Zambrano et al. (2006)	10 (22)	20 (16)

Table 2.

Experimental design characteristics of the high-protein diet studies

	% protein in diet (number of animals)
Studies	Experimental	Control
Carlin et al. (2019)	55 (9)	20 (7)
Daenzer et al. (2002)	40 (22)	20 (33)
Desclée de Maredsous et al. (2016)	55 (8)	20 (8)
Driscoll et al. (1990)	40 (5)	20 (5)
Graves and Wolinsky (1980)	32 (4)	16 (6)
Maurer and Reimer (2011)	40 (6)	20 (6)
Zimanyi et al. (2002)	54 (6)	20 (5)

Litter Size

As shown in Figure 1, there was no significant effect of low-protein diet on litter size when compared with the control; MD χ0.04 pups (−0.19, 0.11; P = 0.62; I² = 0%). High-protein diets (Figure 2) also had no significant effect litter size MD −0.34 g (−1.47, 0.80, P = 0.56; I² = 0%).

Figure 1.

Forest plot of the results from a meta-analysis of the effect of low protein on litter size in rats.

Figure 2.

Forest plot of the results from a meta-analysis of the effect of high protein on litter size in rat.

Litter Weight

Low-protein diets significantly reduced litter weight compared with the control diet as shown in Figure 3; MD −0.56 g (−0.72, −0.40; P < 0.00001; I² = 77%). On the other hand, high-protein diets did not significantly alter litter weight compared with a control diet; MD −0.15 g (−0.40; 0.09, P = 0.22; I² = 60%), see Figure 4.

Figure 3.

Forest plot of the results from a meta-analysis of the effect of low protein on litter weight in rats.

Figure 4.

Forest plot of the results from a meta-analysis of the effect of high protein on litter weight in rats.

Feed Intake

The low-protein diet did not significantly alter feed intake compared with control groups (Figure 5); MD −2.36g (−6.36, 1.65; P = 0.25; I² = 88%). However, a significant reduction was observed in feed intake in the high-protein treatment group compared with the control group (Figure 6); MD –2.13 g (−3.60, −0.66; P = 0.004; I² = 0%).

Figure 5.

Forest plot of the results from a meta-analysis of the effect of low protein on feed intake in rat.

Figure 6.

Forest plot of the results from a meta-analysis of the effect of high protein on feed intake in rats.

Gestational Weight Gain

Animals on the low-protein diet had significantly reduced gestational weight gain when compared with those on the normal protein diet (Figure 7); MD −15.21 g (−23.89, −6.54; P < 0.0006; I² = 59%). Only one study (Zimanyi et al., 2002) reported the effect of high vs. normal protein diet on gestational weight gain in rats and no significant difference was noted between the treatment and control groups (Figure 8); MD 5.50 g (−5.96, 16.96; P = 0.35).

Figure 7.

Forest plot of the results from a meta-analysis of the effect of low protein on gestational weight gain in rats.

Figure 8.

Forest plot of the results from a meta-analysis of the effect of high protein on gestational weight gain in rats.

Publication Bias

The funnel plots for all analyses (S2–S9) can be seen in the supplementary data file. Subsequent trim-and-fill analyses identified evidence of publication bias. Trim-and-fill analysis estimated no change in the MD for the effect of high protein on feed intake (MD_E = −2.13). Trim-and-fill analysis estimated a decrease in the MD for the: effect of high protein on litter size (MD_E = −0.56), effect of high protein on litter weight (MD_E = −0.21), effect of low protein on feed intake (MD_E = −4.02). Trim-and-fill analyses estimated an increase in the MD for the: effect of low protein on litter size (MD_E = −0.03), effect of low protein on gestational weight gain (MD_E = −9.50). Trim-and-fill analysis was unable to be completed for the effect of high protein on gestational weight gain as only one study was included in the meta-analysis. Trim-and-fill analyses forest plots can be seen in the supplementary data figures S10–S16. While publication bias may be present, the results of the trim-and-fill analyses support our findings of a no significant difference between the experimental and control groups for the: effect of low protein on litter size, effect of high protein on litter size, effect of high protein on litter weight, and effect of low protein on feed intake meta-analyses. The results of the trim-and-fill analysis support our findings of a significant difference between the experimental and control groups for the: effects of low protein on litter weight and effects of high protein on feed intake meta-analyses. The results of the trim-and-fill analysis suggest there may be no significant difference between the experimental and control groups for the effect of low protein on gestational weight gain meta-analysis (Table 3).

Table 3.

Publication bias estimates

Independent variable	$\mathrm{M}{\mathrm{D}}_{\rho }$	$\mathrm{S}{\mathrm{E}}_{\rho }$	95% conf. interval	${\mathrm{z}}_{\rho }$	$\mathrm{M}{\mathrm{D}}_{\mathrm{E}}$	$\mathrm{S}{\mathrm{E}}_{\mathrm{E}}$	95% CI*	$z_{\mathrm{E}}$
Low protein on litter size	−0.03	0.09	−0.18, 0.12	0.45	−0.03	0.08	−0.18, 0.12	0.37
High protein on litter size	−0.19	0.51	−1.18, 0.81	0.37	−0.56	0.44	−1.42, 0.29	1.29
Low protein on weight	−0.50	0.08	−0.66, −0.34	6.11	−0.50	0.08	−0.66, −0.34	6.11
High protein on weight	−0.15	0.13	−0.37, 0.07	1.33	−0.20	0.12	−0.44, 0.04	1.67
Low protein on feed intake	−1.88	2.29	−5.37, 1.60	1.06	−4.02	1.95	−7.85, −0.20	2.06
High protein on feed intake	−1.65	0.71	−3.04, −0.27	2.34	−1.65	0.71	−3.04, −0.27	2.34
Low protein on gestational weight gain	−15.14	4.19	−22.42, −7.86	4.08	−10.72	4.85	−20.23, −1.21	2.21
High protein on gestational weight gain	3.88	5.21	−6.34, 14.10	0.74

$\mathrm{M}{\mathrm{D}}_{\rho }$ = mean difference (summary effect size); $\mathrm{S}{\mathrm{E}}_{\rho }$= standard error of calculated mean difference; ${\mathrm{z}}_{\rho }$ = z-score of calculated mean difference; 95% conf. interval = 95% confidence interval around calculated mean difference; $\mathrm{M}{\mathrm{D}}_{\mathrm{E}}$ = estimated mean difference (summary effect size); $\mathrm{S}{\mathrm{E}}_{\mathrm{E}}$= standard error of estimated mean difference; $z_{\mathrm{E}}$ = z-score of estimated mean difference; 95% CI* = 95% confidence interval around estimated mean difference.

Discussion

Our analysis, to the best of our knowledge, is the first to examine data from randomized dietary trials on gestational outcomes in rats. The pooled data analyses suggest that animals are able to adjust their pattern of reproduction according to the quantity of protein in their available food. Neither low- nor high-protein diets had an effect on litter size compared with a normal protein diet; however, litter weight was lower with low-protein diet but not with a high-protein diet. The low-protein diets resulted in reduced gestational weight.

Litter Size

Our pooled analyses showed no significant effect of dietary protein (both low and high dietary protein vs. normal protein diets) on litter size, suggesting that normal litter size is likely regardless of dietary protein intake in rats during fetal development. This interesting observation may reflect short-term protection against suboptimal protein dietary intake, given that the rats in this analysis were on appropriate protein intake levels prior to gestation. Alternatively, the observed failure of reduced protein intake to influence litter size may reflect an adaptive strategy in the rat, where litter size is maintained at the expense of reduced fetal weight. A previous study observed that increased or reduced protein intake during gestation has no effect on litter size (Sasaki et al., 1982), but litter weight is clearly related to protein intake (Naismith and Morgan, 1976). Engelbregt et al., (2001) reported increased litter size when the nutritional demands of the rat were exceeded. However, in our analysis where the diets were started after conception, increased or decreased dietary protein levels had no effect on the survival of embryos to term.

Litter Weight

Our analysis of 22 studies showed a significant reduction in litter weight with low-protein dietary treatment. Litter weight is an important selection trait and a production measure in animal improvement programs (Rothschild and Bidanel, 1998). Litter weight can be negatively associated with litter size (Freetly and Leymaster, 2004), although our analysis failed to support this observation, the relationship maybe explained by the fact that litter size may be determined by the rate of fetal growth in late gestation (Freetly and Leymaster, 2004). Our findings are consistent with previous studies (Langley-Evans et al., 1994; Woods et al., 2001) that observed that pups of the same dam treated with low gestational dietary protein had lower litter weights. Several rat model studies have shown similar results with low maternal protein intake during pregnancy associated with low birth weight and several conditions resembling human metabolic disorders (Bertram et al., 2001; Fernandez-Twinn et al., 2003; Armitage et al., 2004).

Gestational Weight Gain

While our results identified that low-protein diets resulted in a significantly lower gestational weight gain compared with those animals on the control diet, trim-and-fill analysis demonstrates that there is evidence of publication bias that may influence our findings. The gestational weight gain in the animals on high-protein diets was not significantly different from the control. This is contrary to previous studies that maintained that dietary protein is a successful tool in the prevention of obesity through reductions in BW and fat mass (Santesso et al., 2012; Astrup et al., 2015; Leidy et al., 2015) due to its modulation of energy homeostasis and appetite signaling, leading to reduced feed intake. High dietary protein has been reported to induce weight loss through longer postprandial satiety and increased dietary thermo-genesis leading to reduced energy intake (Lacroix et al., 2004; Pichon et al., 2006; Journel et al., 2012; Santesso et al., 2012; Leidy et al., 2015). Our results on the effect high dietary protein diet are similar to a study in humans (Krieger et al., 2006) who observed no effect of higher protein intake on body mass.

Feed Intake

The results of our analysis of the effect of high- vs. normal-protein dietary intake revealed a significant reduction in feed intake. This result may form a guide for the management of gestational obesity and overweight dams. Our findings are consistent with previous studies which report that unlike other macronutrients, dietary proteins are known for their satiating effect due to secretion of satiety hormones (Krieger et al., 2006; Larsen et al., 2010; Hu et al., 2012; Journel et al., 2012; Wycherley et al., 2012; Phillips, 2014). Belza et al., (2013) reported that the mechanism of appetite regulation and satiety effect of dietary protein is as a result of increased secretion of PYY 3 to 36, GLP-1, and glucagon. Also, Journel et al. (2012) observed in their review that protein diet reduces ghrelin secretion and induces alterations in gluconeogenesis to improve energy metabolism which eventually leads to negative energy balance. Morales et al., (2017) reported that the satiety effect of high-protein diets is generated through increased anorexigenic, and decreased orexigenic hormones, and French et al., (2017) observed a significant reduction in feed intake by the group fed 40% protein compared with those fed a control diet (20% protein).

Our analysis showed that there was no significant effect on ADFI between the low protein and control protein groups. Unfortunately, only one study reported the effect of high-protein diets on feed intake during pregnancy but these data support the study by Lacroix et al. (2004) that increased consumption of dietary protein reduces food intake, but the reasons why feed intake on those animals on low-protein diets did not increase over that of the control is unclear, but it could be that the it requires a much longer time period than just over gestation for the metabolic demands to be sufficient to result in an increased consumption.

Limitations and Strengths

This study was limited to rat studies alone and therefore the results may not be applicable to other species. We also encountered very few studies on some outcome measures especially the effect of high-protein treatment on gestational weight gain, and therefore it was difficult to conduct analyses based on these few articles. Many but not all studies stated the rats were selected randomly so it is possible that this may have contributed to the heterogeneity seen in some analyses. Finally, slight variations due to the amount of protein used may impact on the outcome measures and may lead to raised heterogeneity. Despite these limitations, the strengths of this analysis include a systematic characterization of uncharacterized studies by pooling data from several trials to provide a more useful interpretation of the available data.

Conclusions

In conclusion, our study observed that neither a high- or low-protein diet during gestation affected litter size. However, a low-protein diet did significantly reduce litter weight and gestational weight gain, but had no significant effect on litter size and feed intake. High-protein diet reduced feed intake but had no effect on litter size or litter weight. These results confirm the importance of exercising caution when manipulating gestational diets to achieve enhanced reproductive outcomes and weight management during gestation.

Conflict of interest statement None declared.