Protocol for a prospective cohort study for the assessment of sarcopenia in gestational diabetes: the SiGnal-D study

Abstract

Introduction

Sarcopenia is characterised by loss of muscle mass and strength. Although ageing is the most likely risk factor of sarcopenia, sarcopenia is prevalent even in non-elderly people. Type 2 diabetes (T2D) is a risk factor for sarcopenia, as T2D shares with sarcopenia several aetiological factors. Meanwhile, gestational diabetes mellitus (GDM) is characterised by metabolic alterations that resemble those observed in T2D, including increased insulin resistance (present even in physiologic pregnancies). Hence, GDM presents two major risk factors for sarcopenia, that is, dysglycaemia and insulin resistance. Moreover, the number of pregnancies at age >40 years is increasing, which is in an age range in which sarcopenia prevalence is already not negligible. However, data on the prevalence of sarcopenia prevalence in GDM and its effect on pregnancy outcomes are limited. Thus, this study aims to evaluate the prevalence of sarcopenia in women with GDM (and in pregnant women without GDM), identify risk factors and determine its effect on delivery and maternal and fetal outcomes.

Methods and analysis

For this study, 100 each of women with and without GDM will be recruited. Women will undergo an oral glucose tolerance test within weeks 24–28 for possible GDM diagnosis (in weeks 16–18 for high-risk women). Muscle/physical performance tests will be conducted at weeks 28–32 for possible diagnosis of sarcopenia/presarcopenia. Cognitive function will also be assessed. For all women, information regarding pregnancy progression, along with any complications, will be collected. Collected data will be analysed according to the main objectives of the study: (i) determine the prevalence of sarcopenia/presarcopenia in pregnancy with and without GDM, (ii) identify factors associated with sarcopenia risk, (iii) determine the effect of sarcopenia/presarcopenia on pregnancy outcomes, (iv) explore the relationship between sarcopenia and cognitive function. Therefore, this study will provide information on sarcopenia/presarcopenia prevalence in GDM and, possibly, in pregnancy not complicated by dysglycaemia. Furthermore, the study will provide knowledge on the main factors associated with sarcopenia/presarcopenia in GDM/pregnancy. The identification of such factors will be relevant for an initial guidance for treatments that may prevent sarcopenia in GDM/pregnant women. This will become of even greater interest if sarcopenia/presarcopenia influences pregnancy outcomes, especially in GDM women.

Ethics and dissemination

The study protocol has been approved by the Comitato Etico Regione Toscana - Area Vasta Nord Ovest (CEAVNO) on 25 July 2024 and by the Local Ethics Committee of the Medical University of Vienna on 17 June 2024. Participants’ enrolment began in May 2025. The results of the study will be presented at national and international conferences and in peer-reviewed journals.

Trial registration number

ClinicalTrials.gov Identifier: NCT06876090; Registration Date: 2025-03-14

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• We describe a protocol for a prospective cohort study for the assessment of sarcopenia in gestational diabetes (GDM) and, possibly, even in pregnancy not complicated by dysglycaemia.

• The prospective cohort study will be carried out on the basis of the described protocol and will provide data on the prevalence of sarcopenia (or presarcopenia) in GDM, as well as, possibly, in pregnancy in general.

• Additionally, the prospective cohort study based on the described protocol will investigate the potential association of sarcopenia with adverse maternal, fetal, neonatal and perinatal outcomes.

• A limitation of the study protocol is that long-term follow-up of the mothers and newborns has not been planned.

• At the moment, the prospective study will be conducted mainly in women of Caucasian ethnicity.

Introduction

Sarcopenia is a syndrome characterised by the loss of skeletal muscle mass (SM) and strength, with risk of adverse outcomes such as poor quality of life, physical disability and even death.¹ Recently, associations between sarcopenia and impaired cognitive function have been described as well.²

Reduced muscle mass, along with low muscle strength or low physical performance, is required for the diagnosis of sarcopenia.^{3 4} The concomitance of the three factors characterises severe sarcopenia. Conversely, isolated muscle mass loss is better defined as presarcopenia.⁵ With regard to the underlying mechanisms, age-related sarcopenia (ie, primary sarcopenia) and secondary sarcopenia could be differentiated when other factors such as malnutrition (inadequate dietary intake of energy and/or proteins), insufficient physical activity and presence of other diseases or disorders play a pathogenetic role.⁶ Comorbidities favouring sarcopenia include gastrointestinal diseases (malabsorption), organ failure (eg, heart, kidneys, lungs, brain and liver), inflammatory diseases, cancer, neurodegenerative diseases and metabolic/endocrine disorders or diseases (insulin resistance, T2D and obesity). In addition, the coexistence of sarcopenia and obesity identifies a specific sarcopenic phenotype, also known as sarcopenic obesity. Moreover, cachexia is often associated with sarcopenia,⁷ and pharmacological agents (such as corticosteroids) can also increase sarcopenia risk.⁸ Of note, sarcopenia may be prevented,⁹ but once manifest, remission is not common. However, pharmacological intervention and adequate physical exercise can mitigate the clinical picture.¹⁰

In recent years, the prevalence of sarcopenia has been reported to increase. A recent review/meta-analysis analysed 151 studies for a total of 692 056 participants.¹¹ Sarcopenia prevalence ranged from 10% to 27% at age ≥60 years and, surprisingly, from 8% to 36% in individuals aged <60 years. This meta-analysis¹¹ showed that although ageing is the most likely risk factor for sarcopenia, this condition can be prevalent even in non-elderly people. This is clearly shown in studies in which the prevalence of sarcopenia was reported in different age categories.12,14 Pongchaiyakul et al¹² (832 participants) reported that the prevalence of sarcopenia ranged from 11% to 36% until age 49 years. Bae et al¹³ (17 968 participants) reported a sarcopenia prevalence of 19.2% in the group aged 20–39 years. Cho et al¹⁴ reported a lower, yet remarkable, prevalence of 9% in the group aged <50 years (8092 participants, average age 38 years).

As mentioned above, type two diabetes (T2D) is a risk factor for sarcopenia. The most likely reason is that T2D shares with sarcopenia several aetiological factors, such as inflammation, oxidative stress, insulin resistance, cardiovascular comorbidities, low physical activity, malnutrition and ageing.^{15 16} Meanwhile, GDM is characterised by metabolic alterations similar to those of T2D (mainly insulin resistance and beta-cell dysfunction),¹⁷ although its most distinctive trait is insulin resistance.¹⁸ In fact, owing to hormonal changes during pregnancy, a certain degree of insulin resistance develops even in physiological pregnancies.¹⁹ Hence, GDM presents at least two major risk factors for sarcopenia, that is, dysglycaemia and severe insulin resistance. Moreover, the number of pregnancies at age >40 years is increasing, which is an age range in which the prevalence of sarcopenia is already sizeable.12,14 Nevertheless, data are lacking regarding the prevalence of sarcopenia in women with GDM and its potential effects on maternal, fetal and neonatal health. Thus, we plan to evaluate sarcopenia prevalence in women with GDM (as well as in pregnant women without GDM), identify risk factors and determine the potential impact on pregnancy outcomes.

Methods and analysis

Study outcomes

The main objectives of the study are:

1. To determine the prevalence of sarcopenia/presarcopenia in pregnant women with and without GDM.

2. To identify pre-gestational and gestational factors that may be associated with the risk of developing or worsening existing sarcopenia.

3. To determine the potential association of sarcopenia/presarcopenia to pregnancy outcomes, including pregnancy complications, fetal growth by gestational age, type of delivery and delivery complications, newborn health and metabolic status.

4. To explore the relationship between sarcopenia, cognitive function and neuronal activity.

Recruitment

Recruitment of the pregnant women has started in May 2025 and will be completed by April 2026, whereas the planned study end date is April 2027. Eligible participants must be of Caucasian ethnicity, willing to participate in the study and have at least one of the following conditions: (i) age ≥35 years, (ii) body mass index (BMI) ≥25 kg/m², (iii) glycaemia between 5.6 and 6.9 mmol/L before or at the beginning of pregnancy, (iv) fetal macrosomia in a previous pregnancy, (v) GDM in a previous pregnancy and (vi) first-degree family history of diabetes. The final inclusion criterion is the ability to comprehend Italian or English language for women recruited in Pisa, Italy (at the Azienda Ospedaliero Universitaria Pisana, connected to the Department of Clinical and Experimental Medicine, University of Pisa), and German or English language for women recruited in Vienna, Austria (at the Department of Obstetrics and Gynaecology, Medical University of Vienna). The main exclusion criteria (in addition to not meeting the inclusion criteria) are as follows: a twin pregnancy, presence of any already-known disease/disorder possibly affecting muscle mass or function, neurological or psychiatric diseases and already-known diabetes (eg, type 1 or T2D). The main exit criterion will be the withdrawal of consent. The inclusion and exclusion criteria are the same for women with or without GDM in the current pregnancy.

During the recruitment phase, we expect to perform at least 500 oral glucose tolerance tests (OGTTs) for GDM screening. Based on our previous data, GDM prevalence is approximately 25% of the screened women. Therefore, we expect to diagnose around 120 women with GDM. Based on the inclusion and exclusion criteria and willingness to provide informed consent, we hypothesise an exclusion rate of 15%–20%, leaving us with the potential for recruiting at least 100 women with GDM. An equal number of non-GDM women (average-matched by age and BMI) will also be recruited, thus for a total of at least 200 participants.

Notably, the indicated sample size is related to the study duration. This sample size is in line with information from previous studies: for example, Pongchaiyakul et al¹² reported a sarcopenia prevalence of 11.29% (0% of severe sarcopenia) in the group aged 20–29 years, 22.73% (plus 3.03% severe) in those aged 30–39 years and 23.15% (plus 3.70% severe) in those aged 40–49 years. Bae et al¹³ reported a prevalence of 17.1% in women aged 20–39 years. Cho et al¹⁴ reported 8.6% women aged <50 years. Based on these data, a weighted average of sarcopenia prevalence in women aged <50 years (taking into account the different size of the mentioned studies,12,14 being 236, 3306 and 4965 women, respectively) would be 12.3%. Moreover, the prevalence of sarcopenia may be higher in patients with diabetes than matched individuals without diabetes.²⁰ It is not uncommon to observe a prevalence of ~30% or even higher.^{21 22} Thus, with a hypothesised sarcopenia prevalence of 12.3% in pregnant women without GDM and real-world prevalence of 30% in GDM women, sample size calculation indicates that 83 participants per group are sufficient to show a difference in prevalence between the two groups, at 80% power and two-sided significance level of 0.05 for Pearson’s χ2 test. In fact, one of the aims of this study is to show a possible difference in sarcopenia prevalence between the GDM and non-GDM groups. Notably, since we plan on recruiting at least 100 women in both groups, for the assessment of a possible difference in sarcopenia prevalence between the two groups, a dropout rate of up to 15% will be acceptable.

The study will comply with the standards of good practice for medical research as defined in the Declaration of Helsinki. Written informed consent to study participation will be obtained for all recruited women. The study has already received approval from the local Ethics Committees (University of Pisa and Medical University of Vienna). The study protocol has also been registered at ClinicalTrials.gov (NCT06876090).

Normal pregnancy and gestational diabetes examinations

Before the scheduled date for the screening OGTT (7–10 days before), all women will be preliminarily contacted for a careful description of the study so that they may consider providing written informed consent on the first visit (V1). At V1, recruited women will undergo a 75 g OGTT after an overnight fast. High-risk women for GDM (previous GDM, BMI ≥30 kg/m² and/or glycaemia between 5.6 and 6.9 mmol/L before or at the beginning of pregnancy) will undergo OGTT between weeks 16 and 18. All other women will undergo OGTT at weeks 24–28. High-risk women, with normal OGTT at weeks 16–18, will undergo the test again at weeks 24–28. GDM diagnosis will be based on the criteria of the International Association of Diabetes and Pregnancy Study Group.²³ Blood samples for GDM diagnosis will be collected at 0 (ie, at fasting, immediately before glucose ingestion), 30, 60 and 120 min following glucose ingestion for the measurement of plasma glucose, insulin and C-peptide levels. Before the OGTT, relevant medical and personal history (obstetric history, pre-pregnancy body weight, smoking, dietary and physical activity habits, education level, etc.) will be recorded along with measurement of BMI, blood pressure and heart rate.

At week 28–32, all participants will undergo a haemochromocytometric test (visit V2). On V2, glycated haemoglobin and adipokines (leptin, adiponectin and irisin), relevant for examining the relationships between sarcopenia and inflammation, will also be measured (21). The blood aliquot has been determined and deemed acceptable for pregnant women. Moreover, as for clinical routine, all women will undergo a further blood (and urine) test at weeks 35–37 (V3). On V3, if needed, tests of one or more of the variables required for the study may be repeated. At our centres, some additional visits/examinations are routinely performed for pregnant women, particularly for GDM, including, among others, obstetric echography and cardiotocography. Although these further visits/examinations currently do not appear of major relevance for our study aims, related data will be available if we identify any potential usefulness for the study. Figure 1 summarises the sequence of visits that participants will undergo during pregnancy (excluding the routine pregnancy visits not specifically related to our study).

Figure 1. Flow diagram of the pregnancy visits and tests. fNIRS, functional near-infrared spectroscopy; GDM, gestational diabetes; OGTT, oral glucose tolerance test; V1, visit 1; V2, visit 2; V3, visit 3.

Muscle mass, strength and physical performance (sarcopenia-related parameters)

Examinations related to muscle mass and strength, and to the degree of physical performance, will be accomplished in the third trimester of pregnancy, as major body composition changes occur at this time. Thus, since one of the main aims of the project is to determine muscle mass, strength and physical performance, the third trimester appears to be the most appropriate period for the assessment of sarcopenia-related parameters. Precisely, muscle/physical performance tests will be performed at weeks 28–32. At the time being, we hypothesise performing these evaluations on V2. However, if this would be an excessive burden to the pregnant women, it will be planned on a separate day, still between weeks 28 and 32.

Diagnosis of sarcopenia/presarcopenia will be based on the 2010 criteria of European Working Group on Sarcopenia in Older People (EWGSOP).³ Presarcopenia is diagnosed based solely on the presence of low muscle mass. For sarcopenia, in addition to low muscle mass, low muscle strength and/or low physical performance need to be determined, and sarcopenia is defined as ‘severe’ if all signs are present. EWGSOP indicated different techniques for sarcopenia/presarcopenia testing. In the present case, simple, non-invasive and not time-consuming techniques are preferred. Therefore, muscle mass will be tested by bioelectrical impedance analysis (BIA), muscle strength by handgrip strength test and physical performance by the usual gait speed test.³ Specifically, BIA will be performed using a professional body composition analyser (with specific indication for use during pregnancy). This medical device can estimate skeletal muscle mass (SM) and other body parameters, such as lean and fat body mass, intracellular and extracellular body water and dry lean mass (ie, protein and mineral body content). Of relevance, BIA has already been used in several studies involving pregnant women, as summarised in a recent review.²⁴ Handgrip strength will be assessed by a professional hydraulic dynamometer. The usual gait speed test will be performed by asking the women to walk at natural speed over a uniform path of prescribed length (typically, 6–10 m). The time required for walking that distance will be recorded by a chronometer. A flow diagram of the test sequence is provided in figure 2.

Figure 2. Flow diagram of the sarcopenia tests. BIA, bioelectrical impedance analysis.

Studies in sarcopenia/presarcopenia have suggested somewhat different cut-off values for the parameters derived by the indicated tests. For the BIA-derived SM, we will refer to the cut-off reported by Chien et al,²⁵ which suggests normalisation of SM by height squared (ie, skeletal muscle mass index (SMI), equal to SM/height²). In women, low SMI is assumed for SMI <6.42 kg/m². We have opted for this cut-off, compared with some slightly different ones,^{26 27} because the former has been suggested by studying young rather than elderly people (although the study also included elderly people, analysed separately²⁵). Thus, for the present study, the indicated cut-off appears more appropriate than others, in relation to the typical age of pregnant women. The cut-off for muscle mass strength, as derived by the handgrip test, was suggested by Lauretani et al.²⁸ In women, low muscle strength is defined as handgrip strength below 20 kg. However, we will also consider cut-off values specific for different BMI intervals (28). The cut-off for gait speed was also suggested by Lauretani et al²⁸ (low speed: <0.8 m/s). Finally, we will assess the effect of sarcopenia/presarcopenia prevalence on our population when considering some updated criteria and cut-off values, such as, although not exclusively, those reported in the 2019 guidelines of EWGSOP (named as EWGSOP2).⁴

Cognitive function and lifestyle questionnaires

Cognitive impairment has been demonstrated in sarcopenia, especially related to low muscle strength.² This may be due to the direct cross-talk between the muscles and the brain, mediated by exercise-induced myokine release (also named as ‘exerkines’). We will assess cognitive function using one or two questionnaires, likely the Montreal Cognitive Assessment²⁹ and/or the Trail Making Test.³⁰ All women will be asked to fill out the questionnaire(s) immediately after the sarcopenia-related tests.

Information on lifestyle will also be useful to complement the sarcopenia-related parameters as described above. Thus, on the same occasion of the sarcopenia and cognitive function tests, a questionnaire on nutritional habits and physical activity will be administered to all women, asking them to fill it out and send it back within 1 week (by email or ordinary mail). Of note, nutritional counselling will be provided for the whole project duration.

Functional near-infrared spectroscopy

On a voluntary basis, women will also be offered to undergo functional near-infrared spectroscopy (fNIRS) examination. Women agreeing to this option will undergo the fNIRS test at V2, during the handgrip test. The rationale for this examination is that compromised nervous system function has been suggested as one of the important contributors to sarcopenia.³¹ In fact, dopaminergic downregulation, inadequate motor programming and motor coordination impairment can lead to a decline in supraspinal drive. In addition, motor unit reorganisation and inflammatory changes in motor neurons can decrease conduction velocity and amplitude of compound muscle action potential. Furthermore, neuromuscular junction remodelling may contribute to neuromuscular impairment.³¹

The fNIRS tests will be performed by using OxyMon, plus fNIRS/electroencephalography (EEG) headcap (Artinis Medical Systems, The Netherlands). Women will wear the headcap, which allows detecting fNIRS (and optionally EEG) signals from various cortex areas by special electrodes (‘optodes’). The headcap is connected to the OxyMon system that registers the signals and performs appropriate signal processing. The system measures changes in oxyhaemoglobin, deoxyhaemoglobin and total haemoglobin concentrations. For higher reliability, women will perform the handgrip test two times, with a prescribed time interval for resting. The system will register the fNIRS signals during the whole test session, which included two handgrip tests and a rest time in between. The data will then be analysed using commercial tools and custom-made software for advanced analysis of signal variability (fractal dimension, detrended fluctuations, approximate entropy, etc.). Of note, exploitation of the handgrip test as a motor task for fNIRS investigation in sarcopenia is consistent with what was done in previous studies.³² Moreover, fNIRS has already been used in pregnancy and specifically in GDM,³³ thus indicating the safety of this examination in those conditions.

Data on pregnancy progression, delivery, newborn health status and postpartum examinations

For all women included in the study, all information regarding the usual evaluation of pregnancy, including obstetric echography, cardiotocography, ultrasound evaluation of the amniotic fluid and fetal growth will be collected. Moreover, the time and type of delivery will be recorded along with any complication. Newborn information will include sex, length, weight and appearance, pulse, grimace, activity and respiration score. Feeding information will also be collected.

At week 6–12 postpartum (V1POST), a diagnostic OGTT will be performed in women who had GDM to screen for possible diabetes or pre-diabetes. In addition, for our specific study aims, a subgroup of women will be recalled for a follow-up visit (V2POST) at month 6 postpartum (±2 weeks). On that occasion, sarcopenia tests will be repeated, and further OGTT will be performed (similar to that at V1, ie, four samples, and glucose, insulin and C-peptide measures). Other relevant blood tests will also be repeated. Women will also be asked to fill out questionnaires again (plus fNIRS, optionally). We plan on recalling about 50% of study participants, and criteria will be precisely defined based on the baseline findings (likewise, women who already have sarcopenia/presarcopenia at baseline and/or with abnormal values of sarcopenia-related parameters, eg, in the worst quartile for one or more of such parameters).

Data analyses

Collected data will undergo quality control, based on visual inspection of data distributions and on checks through automatic procedures that identify abnormalities, both in terms of absolute variable value and/or relative to other variable values, considering the specific population under analysis (pregnant and GDM women, in this case).

Moreover, by mathematical modelling of the OGTT data, we will calculate insulin sensitivity, insulin secretion, pancreatic beta-cell function and insulin clearance. Insulin sensitivity deterioration (ie, insulin resistance) is a typical trait of both sarcopenia and GDM (and partly of normal pregnancy). Thus, we will analyse this aspect in detail, using different insulin sensitivity/resistance indices. Indeed, OGTT-based indices are surrogate markers of the ‘reference’ insulin sensitivity as determined by the clamp technique,³⁴ which is, however, hardly feasible in the clinical routine. The validated OGTT-derived indices are typically good markers of the clamp-derived index, but some differences may be shown among different OGTT indices, especially in specific conditions.³⁵ Sarcopenia and GDM are certainly a peculiar ‘combined’ condition that may determine the unreliability of some indices. If all (or the majority of) indices will provide consistent information, this would be a clue to their reliability. In contrast, if indices provide conflicting results, this calls for the need for new, ‘specialised’ indices. In this case, appropriate modelling and statistical analyses will be performed to derive a new index/method by also exploiting BIA data. Indices that will be computed are our recently developed PREDIM,³⁶ and the more traditional OGIS,³⁷ ISIcomp,³⁸ MCRest³⁹ and SIoral⁴⁰ (and, possibly, some others, such as CLIX⁴¹).

Insulin secretion and beta-cell function will be assessed by mathematical modelling that allows calculation of different aspects of the beta-cell behaviour.^{42 43} Briefly, the main beta-cell function parameters that will be derived from the model are as follows: (i) beta-cell glucose sensitivity (the mean value of the dose–response function, describing the dependence of insulin secretion on absolute glucose concentration), (ii) rate sensitivity (proportionality constant of the derivative component of the secretion, representing the dynamic dependence of secretion on the rate of change of glucose), (iii) ratio of the potentiation function at 120 to that at 0 min (explaining the sustained insulin secretion levels that are typically seen at the end of an OGTT in healthy participants, when glucose has already returned to baseline). Another interesting parameter is insulin secretion at the reference glucose value. Insulin clearance will be derived from insulin secretion and plasma insulin levels. Furthermore, on the basis of the clinical variables that we will measure in addition to the OGTT, we may compute other indices of potential interest in glucose metabolism, such as the triglyceride–glucose index⁴⁴ and the SPISE index.⁴⁵

Statistical analyses

Data distributions will be assessed by graphical tests, and appropriate actions will be taken in case of skewed distributions (such as use of non-parametric tests or log-transformation). Differences in the prevalence of sarcopenia in GDM vs non-GDM women will be assessed with Pearson’s χ test. Based on the OGTT and sarcopenia tests during pregnancy, participants will be stratified into two groups (GDM and non-GDM) and four subgroups: SARCO-GDM, nonSARCO-GDM, SARCO-nonGDM, nonSARCO-nonGDM (where ‘SARCO’ indicates the presence of sarcopenia (or presarcopenia) and ‘nonSARCO’ indicates absence of sarcopenia/presarcopenia). We will test for possible differences among the indicated subgroups in the glucometabolic parameters (such as insulin sensitivity/resistance), sarcopenia-related parameters and other collected variables by the analysis of variance, whereby Tukey’s post-hoc test will be used to achieve a 95% coverage probability. Analyses will also be performed in groups/subgroups appropriately pooled.

Moreover, correlation analyses (such as Spearman’s rho) will be used to assess possible associations among the sarcopenia-related parameters and the glucometabolic parameters, as well as the other collected variables (again, in groups/subgroups separated and/or pooled). Of note, we will perform both univariable and multivariable regression analyses, possibly driven by specific variable selection techniques, such as stepwise regression analysis (or more advanced shrinkage regression).

With follow-up data, it will be possible to identify baseline predictors of sarcopenia/presarcopenia at later time points (though in a relatively short period, due to project duration). Predictive accuracy, sensitivity and specificity will be tested by receiver operating characteristic curves.

Furthermore, we will analyse the time trend of sarcopenia-related parameters (muscle mass and strength and physical performance) by appropriate methods such as linear mixed effects models. Machine learning techniques will also be applied for robust regression and classification analyses. In the case of missing data in some variables, we will consider applying data imputation techniques, such as multiple imputation by chained equations. Statistical analyses will be performed with R and contributed packages. A two-sided type 1 error rate of 0.05 will be considered statistically significant. However, all p-values will be interpreted in an explorative manner to generate new hypotheses.

Discussion

The study presented will provide information on sarcopenia and presarcopenia prevalence in GDM and, possibly, in pregnancy uncomplicated by dysglycaemia. Furthermore, the study will provide knowledge on the main glucometabolic factors associated with sarcopenia or presarcopenia (or, at any rate, associated with the possible worsening of the physiological variables on which sarcopenia/presarcopenia diagnosis is based). In addition, we will analyse factors other than the glucometabolic ones that may show possible association with sarcopenia (for instance, inflammatory factors). The baseline careful characterisation of the study population, coupled with the planned follow-up, will also set the basis for identifying predicting factors. The identification of such factors will be of major importance, as it may represent an initial guidance for treatments that may prevent sarcopenia in GDM/pregnant women. This will become of even greater interest to the extent that sarcopenia/presarcopenia may affect progression and outcomes of pregnancy, in particular in women with GDM.

Notably, when sarcopenia develops, spontaneous remission has rarely been observed. However, several studies have shown that sarcopenia can be mitigated or even reverted by pharmacological intervention46,48 or proper physical exercise, such as ‘resistance-type exercise’ training.¹⁰ Thus, with appropriate intervention, possible GDM-induced sarcopenia/presarcopenia may be mitigated/reverted as well and, likely, even prevented.

Another achievement of the study will be the possible identification of sarcopenia/presarcopenia as a further risk factor for GDM (in addition to those already known as GDM risk factors49,51). Although the focus of the study is to investigate how GDM may lead to sarcopenia, sarcopenia may contribute to GDM. This has been suggested in the case of T2D, where the relationship between sarcopenia and T2D has been defined as ‘bidirectional’.⁵²

Another novel aspect is the evaluation of cognitive and neuronal function. Much emphasis is currently paid on what has been suggested to be a new diabetic ‘complication’,⁵³ but little is known about it in GDM. Our investigation is of relevance because it exploits recent information linking sarcopenia and cognitive function, combining functional tests with direct neuronal exploration with a state-of-the-art approach. Due to its nature and duration, the project cannot answer all questions on this aspect; however, it can be the basis for further scientific investigations.

Is it possible to foresee direct clinical impact for our study? We believe it is, first, because the tests that we have chosen to diagnose sarcopenia/presarcopenia are simple and totally non-invasive. We have selected such tests among others currently available,^{3 4} with the specific purpose of having the opportunity to translate this methodology from the clinical trial to the clinical routine. Thus, the methodology we will use for diagnosing sarcopenia can be considered in clinical practice for women with GDM who harbour one or more factors (predictors) associated with sarcopenia or presarcopenia. Notably, many of the factors that we will analyse are already part of the clinical routine for management of GDM (or even normal pregnancy). Therefore, in our opinion, there is an immediate potential for translating our results into the clinical setting.

Ethics and dissemination

The protocol has been approved by the Comitato Etico Regione Toscana - Area Vasta Nord Ovest (CEAVNO) on 25 July 2024 (ID 25652) and by the Local Ethics Committee of the Medical University of Vienna on 17 June 2024 (n. 1458/2024). All participants to the study will be asked to provide written informed consent to participate in the study. Participant enrolment began in May 2025. We will present the results of the study at national and international conferences and in peer-reviewed journals, with special interest in open-access journals. Special focus for dissemination will be paid to communications at the Conferences of the Italian Diabetes Society, Austrian Diabetes Association, German Diabetes Association and European Association for the Study of Diabetes.